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github | petercorke/machinevision-toolbox-matlab-master | moments.m | .m | machinevision-toolbox-matlab-master/moments.m | 2,348 | utf_8 | 1202c3e5b3a7cea5e2a7db5c22e6167d | %MOMENTS return moment vector for given camera orientation
%
% N = MOMENTS(RPY, V, DISPFLAG)
%
% where RPY is a 3-vector of roll-pitch-yaw angle,
% V are the 3D object vertices,
% DISPLAY is true if a camera's eye view is to be displayed.
%
% Camera parameters are hard-wired as per thesis example.
%
fu... |
github | petercorke/machinevision-toolbox-matlab-master | iconcat.m | .m | machinevision-toolbox-matlab-master/iconcat.m | 3,154 | utf_8 | 5c86e01240e7487adabb1de28df95dff | %ICONCAT Concatenate images
%
% C = ICONCAT(IM,OPTIONS) concatenates images from the cell array IM.
%
% ICONCAT(IM,OPTIONS) as above but displays the concatenated images
% using IDISP.
%
% [C,U] = ICONCAT(IM,OPTIONS) as above but also returns the vector U whose
% elements are the coordinates of the left (or top in ver... |
github | petercorke/machinevision-toolbox-matlab-master | loadinr.m | .m | machinevision-toolbox-matlab-master/loadinr.m | 1,761 | utf_8 | 3e8f6d795d76ced491a64d823d81191d | %LOADINR Load an INRIMAGE format file
%
% LOADINR(filename, im)
%
% Load an INRIA image format file and return it as a matrix
%
% SEE ALSO: saveinr
%
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it... |
github | petercorke/machinevision-toolbox-matlab-master | saveppm.m | .m | machinevision-toolbox-matlab-master/saveppm.m | 1,367 | utf_8 | 5665e744d35554414b5c450169d35d3a | %SAVEPPM Write a PPM format file
%
% SAVEPPM(filename, r, g, b)
% SAVEPPM(filename, rgb)
%
% Saves the specified red, green and blue planes in a binary (P6)
% format PPM image file.
%
% SEE ALSO: loadppm
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB... |
github | petercorke/machinevision-toolbox-matlab-master | colorspace.m | .m | machinevision-toolbox-matlab-master/colorspace.m | 16,190 | utf_8 | e2b11a944eb9f8080dc451493817396a | function varargout = colorspace(Conversion,varargin)
%COLORSPACE Transform a color image between color representations.
% B = COLORSPACE(S,A) transforms the color representation of image A
% where S is a string specifying the conversion. The input array A
% should be a real full double array of size Mx3 or MxN... |
github | petercorke/machinevision-toolbox-matlab-master | yuvopen.m | .m | machinevision-toolbox-matlab-master/yuvopen.m | 1,460 | utf_8 | f29b915c0895563adf8777609927a776 | %YUVOPEN Open a YUV4MPEG file
%
% yuv = yuvopen(frame)
%
% Open a yuv4mpeg format file. This contains uncompressed color
% images in 4:2:0 format, with a full resolution luminance plane
% followed by U and V planes at half resolution both directions.
%
% SEE ALSO: yuvread yuvclose
% Copyright (C) 1993-2011, by Pete... |
github | petercorke/machinevision-toolbox-matlab-master | flatfield.m | .m | machinevision-toolbox-matlab-master/flatfield.m | 1,397 | utf_8 | 8c13f7fadbe7e065bf21ad046fbcaa47 | %FLATFIELD correct lighting unevenness
%
% iff = flatfield(im)
% iff = flatfield(im, mask)
%
% A least squares method is used to fit a plane to the image data. The value
% of the lighting function is returned.
%
% If mask is given a maximum filter of dimension mask x mask is run over the
% data prior to fitting.
% C... |
github | petercorke/machinevision-toolbox-matlab-master | camcalp_c.m | .m | machinevision-toolbox-matlab-master/camcalp_c.m | 2,857 | utf_8 | 148d7a2e8f74dd3bf7117b6eee20a715 | %CAMCALP_C Camera calibration matrix from parameters (central projection)
%
% C = CAMCALP_C(cp)
% C = CAMCALP_C(cp, Tcam)
% C = CAMCALP_C(cp, pC, x, z)
%
% Compute a 3x4 camera calibration matrix from given camera intrinsic
% and extrinsic parameters.
% CP is a camera parameter vector comprising:
% cp(1) f, th... |
github | petercorke/machinevision-toolbox-matlab-master | lspcd.m | .m | machinevision-toolbox-matlab-master/lspcd.m | 2,071 | utf_8 | e67de9778584a673b9569720ea4c72f9 | %LSPCD List attributes of PCD format files
%
% LSPCD() list the attributes of all .PCD files in the current folder.
%
% LSPCD(FILESPEC) as above but list only files that match FILESPEC which
% might contain a directory name and/or a wildcard.
%
%
% See also pclviewer, loadpcd.
%
% Copyright (C) 2013, by Peter I. Corke... |
github | petercorke/machinevision-toolbox-matlab-master | kosecka.m | .m | machinevision-toolbox-matlab-master/kosecka.m | 2,170 | utf_8 | eca1e87daf74e53c8fb6f1816af1563b | % [Sol] = homography2Motion(H)
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Founda... |
github | petercorke/machinevision-toolbox-matlab-master | crop.m | .m | machinevision-toolbox-matlab-master/crop.m | 902 | utf_8 | 15a8b6a0447ccec1ed2ea4edd330eefb | %CROP
%
% im = crop(im)
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Foundation, e... |
github | petercorke/machinevision-toolbox-matlab-master | iendpoint.m | .m | machinevision-toolbox-matlab-master/iendpoint.m | 2,119 | utf_8 | 0d5e7b4e79dc15816a486542ed71e3a9 | %IENDPOINT Find end points in a binary skeleton image
%
% OUT = IENDPOINT(IM) is a binary image where pixels are set if the
% corresponding pixel in the binary image IM is the end point of a
% single-pixel wide line such as found in an image skeleton. Computed
% using the hit-or-miss morphological operator.
%
% Refe... |
github | petercorke/machinevision-toolbox-matlab-master | colorseg2.m | .m | machinevision-toolbox-matlab-master/colorseg2.m | 1,177 | utf_8 | 4a702da2ae9453a5135318b989e937f5 |
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Foundation, either version 3 of the Li... |
github | petercorke/machinevision-toolbox-matlab-master | colorize2.m | .m | machinevision-toolbox-matlab-master/colorize2.m | 920 | utf_8 | bc048caf3e09ca12c4f30806cf5aa1f0 |
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Foundation, either version 3 of the Li... |
github | petercorke/machinevision-toolbox-matlab-master | camparam.m | .m | machinevision-toolbox-matlab-master/camparam.m | 1,259 | utf_8 | 1d2bd4eebd0727ec98eb4860cbb8c2f8 | %CAMPARAM Default camera calibration parameters
%
% ci = camparam
%
% Return a camera intrinsic parameter structure:
% focal length 8mm
% pixel size 10um square
% image size 1024 x 1024
% principal point (512, 512)
%
%
% SEE ALSO: camcalp, pulnix
% Copyright (C) 1993-2011, by Peter I. Corke
... |
github | petercorke/machinevision-toolbox-matlab-master | isift.m | .m | machinevision-toolbox-matlab-master/isift.m | 6,337 | utf_8 | f4489aa2a95779e4d07d9034dc55aad0 | %ISIFT SIFT feature extractor
%
% SF = ISIFT(IM, OPTIONS) is a vector of SiftPointFeature objects
% representing scale and rotationally invariant interest points in the
% image IM.
%
% Options::
% 'nfeat',N set the number of features to return (default Inf)
% 'suppress',R set the suppression radius (defa... |
github | petercorke/machinevision-toolbox-matlab-master | isamesize.m | .m | machinevision-toolbox-matlab-master/isamesize.m | 2,057 | utf_8 | 0f5ccecaaa08302cb075a27119222ad8 | %ISAMESIZE Automatic image trimming
%
% OUT = ISAMESIZE(IM1, IM2) is an image derived from IM1 that has
% the same dimensions as IM2. This is achieved by cropping and scaling.
%
% OUT = ISAMESIZE(IM1, IM2, BIAS) as above but BIAS controls which part
% of the image is cropped. BIAS=0.5 is symmetric cropping, BIAS<0.5 ... |
github | petercorke/machinevision-toolbox-matlab-master | iconv.m | .m | machinevision-toolbox-matlab-master/iconv.m | 2,261 | utf_8 | 56add7e855ad0d80917ac892758682dd | %ICONV Image cross-correlation
%
% C = ICONV(IM1, IM2, OPTIONS) is the cross-correlation of images IM1 and IM2. The
% smaller image is taken as the kernel and correlated with the larger image.
%
% Options::
% 'same' output image is same size as largest input image (default)
% 'full' output image is larger th... |
github | petercorke/machinevision-toolbox-matlab-master | icanny.m | .m | machinevision-toolbox-matlab-master/icanny.m | 2,060 | utf_8 | 735c57645f489c6d101e4a84f55c9833 | %ICANNY Canny edge detection
%
% E = ICANNY(IM, OPTIONS) is an edge image obtained using the Canny edge
% detector algorithm. Hysteresis filtering is applied to the gradient
% image: edge pixels > th1 are connected to adjacent pixels > th0, those
% below th0 are set to zero.
%
% Options::
% 'sd',S set the standa... |
github | petercorke/machinevision-toolbox-matlab-master | ccxyz.m | .m | machinevision-toolbox-matlab-master/ccxyz.m | 1,671 | utf_8 | 90040db03ae558f94e049bfaa909d6f2 | %CCXYZ XYZ chromaticity coordinates
%
% XYZ = CCXYZ(LAMBDA) is the xyz-chromaticity coordinates (3x1) for illumination
% at wavelength LAMBDA. If LAMBDA is a vector (Nx1) then each row of XYZ (Nx3)
% is the XYZ-chromaticity of the corresponding element of LAMBDA.
%
% XYZ = CCXYZ(LAMBDA, E) is the xyz-chromaticity coo... |
github | petercorke/machinevision-toolbox-matlab-master | h2e.m | .m | machinevision-toolbox-matlab-master/h2e.m | 1,275 | utf_8 | 55bb7b941a7b10fb060b398ae374ee95 | %H2E Homogeneous to Euclidean
%
% E = H2E(H) is the Euclidean representation of a set of homogeneous points H.
%
% In the Toolbox points are represented as by Euclidean coordinates which are
% the columns of a matrix E, and the number of rows is either 2 or 3 to
% represent 2- or 3-dimensional points. Euclidean rep... |
github | petercorke/machinevision-toolbox-matlab-master | icolor.m | .m | machinevision-toolbox-matlab-master/icolor.m | 1,726 | utf_8 | 6c6a8c64e3704f4312bdbac7cac263bd | %ICOLOR Colorize a greyscale image
%
% C = ICOLOR(IM) is a color image C (HxWx3)where each color plane is equal
% to IM (HxW).
%
% C = ICOLOR(IM, COLOR) as above but each output pixel is COLOR (3x1) times
% the corresponding element of IM.
%
% Examples::
%
% Create a color image that looks the same as the greyscale im... |
github | petercorke/machinevision-toolbox-matlab-master | peak2.m | .m | machinevision-toolbox-matlab-master/peak2.m | 4,181 | utf_8 | 57ee6ee58bc93f71ae3d79f1d34ebe05 | %PEAK2 Find peaks in a matrix
%
% ZP = PEAK2(Z, OPTIONS) are the peak values in the 2-dimensional signal Z.
%
% [ZP,IJ] = PEAK2(Z, OPTIONS) as above but also returns the indices of the
% maxima in the matrix Z. Use SUB2IND to convert these to row and column
% coordinates
%
% Options::
% 'npeaks',N Number of peak... |
github | petercorke/machinevision-toolbox-matlab-master | iscalemax.m | .m | machinevision-toolbox-matlab-master/iscalemax.m | 2,289 | utf_8 | bd7c233f428ffb47260366f3ad1cfc11 | %ISCALEMAX Scale space maxima
%
% F = ISCALEMAX(L, S) is a vector of ScalePointFeature objects which are
% the maxima, in space and scale, of the Laplacian of Gaussian (LoG)
% scale-space image sequence L (HxWxN). S (Nx1) is a vector of scale values
% corresponding to each plane of L.
%
% If the pixels are considere... |
github | petercorke/machinevision-toolbox-matlab-master | irotate.m | .m | machinevision-toolbox-matlab-master/irotate.m | 3,039 | utf_8 | 3d2f81053a715bbd6effbfd76d1b9ace | %IROTATE Rotate image
%
% OUT = IROTATE(IM, ANGLE, OPTIONS) is a version of the image IM
% that has been rotated about its centre.
%
% Options::
% 'outsize',S set size of output image to HxW where S=[W,H]
% 'crop' return central part of image, same size as IM
% 'scale',S scale the image size by S (de... |
github | petercorke/machinevision-toolbox-matlab-master | ismooth.m | .m | machinevision-toolbox-matlab-master/ismooth.m | 1,907 | utf_8 | c067dd1e285998e6100db0e07e53b8c9 | %ISMOOTH Gaussian smoothing
%
% OUT = ISMOOTH(IM, SIGMA) is the image IM after convolution with a
% Gaussian kernel of standard deviation SIGMA.
%
% OUT = ISMOOTH(IM, SIGMA, OPTIONS) as above but the OPTIONS are passed
% to CONV2.
%
% Options::
% 'full' returns the full 2-D convolution (default)
% 'same' returns ... |
github | petercorke/machinevision-toolbox-matlab-master | inormhist.m | .m | machinevision-toolbox-matlab-master/inormhist.m | 1,524 | utf_8 | 009dad2c14042b5638e86c65e99f2ae4 | %INORMHIST Histogram normalization
%
% OUT = INORMHIST(IM) is a histogram normalized version of the image IM.
%
% Notes::
% - Highlights image detail in dark areas of an image.
% - The histogram of the normalized image is approximately uniform, that is,
% all grey levels ae equally likely to occur.
%
% See also IHIST... |
github | petercorke/machinevision-toolbox-matlab-master | itriplepoint.m | .m | machinevision-toolbox-matlab-master/itriplepoint.m | 2,816 | utf_8 | a9007e2ea1ccaab5a5677d65b12d63de | %ITRIPLEPOINT Find triple points
%
% OUT = ITRIPLEPOINT(IM) is a binary image where pixels are set if the
% corresponding pixel in the binary image IM is a triple point, that is where
% three single-pixel wide line intersect. These are the Voronoi points in
% an image skeleton. Computed using the hit-or-miss morpho... |
github | petercorke/machinevision-toolbox-matlab-master | iblobs.m | .m | machinevision-toolbox-matlab-master/iblobs.m | 7,680 | utf_8 | 6ff982feb79a12b4040b015fac07f258 | %IBLOBS Blob features
%
% F = IBLOBS(IM, OPTIONS) is a vector of RegionFeature objects that
% describe each connected region in the image IM.
%
% Options::
% 'pixelaspect',A set pixel aspect ratio, default 1.0
% 'connect',C set connectivity, 4 (default) or 8
% 'greyscale' compute g... |
github | petercorke/machinevision-toolbox-matlab-master | colorkmeans.m | .m | machinevision-toolbox-matlab-master/colorkmeans.m | 4,527 | utf_8 | a90521529ec386fa4b723084dbb2c4a3 | %COLORKMEANS Color image segmentation by clustering
%
% L = COLORKMEANS(IM, K, OPTIONS) is a segmentation of the color image IM
% into K classes. The label image L has the same row and column dimension
% as IM and each pixel has a value in the range 0 to K-1 which indicates
% which cluster the corresponding pixel bel... |
github | petercorke/machinevision-toolbox-matlab-master | ipixswitch.m | .m | machinevision-toolbox-matlab-master/ipixswitch.m | 4,419 | utf_8 | ae3f240df5bb537629818d67b8ff393b | %IPIXSWITCH Pixelwise image merge
%
% OUT = IPIXSWITCH(MASK, IM1, IM2) is an image where each pixel is
% selected from the corresponding pixel in IM1 or IM2 according to the
% corresponding pixel values in MASK. If the element of MASK is zero IM1 is
% selected, otherwise IM2 is selected.
%
% IM1 or IM2 can contain a c... |
github | petercorke/machinevision-toolbox-matlab-master | mpq.m | .m | machinevision-toolbox-matlab-master/mpq.m | 997 | utf_8 | 060acdd1de075d703b03e53715f1f1ec | %MPQ Image moments
%
% M = MPQ(IM, P, Q) is the PQ'th moment of the image IM. That is, the sum
% of I(x,y).x^P.y^Q.
%
% See also MPQ_POLY, NPQ, UPQ.
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it ... |
github | petercorke/machinevision-toolbox-matlab-master | upq_poly.m | .m | machinevision-toolbox-matlab-master/upq_poly.m | 1,505 | utf_8 | 13cc17a366a33c6c2676af351f3718b2 | %UPQ_POLY Central polygon moments
%
% M = UPQ_POLY(V, P, Q) is the PQ'th central moment of the polygon with
% vertices described by the columns of V.
%
% Notes::
% - The points must be sorted such that they follow the perimeter in
% sequence (counter-clockwise).
% - If the points are clockwise the moments will al... |
github | petercorke/machinevision-toolbox-matlab-master | epishow.m | .m | machinevision-toolbox-matlab-master/epishow.m | 1,312 | utf_8 | 232663a7c9c4b0ed2515c376d7e97ae4 |
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Foundation, either version 3 of the Li... |
github | petercorke/machinevision-toolbox-matlab-master | ccdresponse.m | .m | machinevision-toolbox-matlab-master/ccdresponse.m | 1,534 | utf_8 | d8b6d9c000b0e8ca3c9bcd6a4dfd95e0 | %CCDRESPONSE CCD spectral response
%
% R = CCDRESPONSE(LAMBDA) is the spectral response of a typical silicon
% imaging sensor at the wavelength LAMBDA [m]. The response is normalized
% in the range 0 to 1. If LAMBDA is a vector then R is a vector of the
% same length whose elements are the response at the correspo... |
github | petercorke/machinevision-toolbox-matlab-master | mvtbdemo.m | .m | machinevision-toolbox-matlab-master/mvtbdemo.m | 3,612 | utf_8 | e2b6be5e2c8e104b8298492ec80e0daa | %MVTBDEMO Machine Vision toolbox demonstrations
%
% Displays popup menu of toolbox demonstration scripts that illustrate:
% - image processing
% - feature extraction
% - visual servoing
%
% Notes::
% - The scripts require the user to periodically hit <Enter> in order to move
% through the explanation.
% - Set ... |
github | petercorke/machinevision-toolbox-matlab-master | klog.m | .m | machinevision-toolbox-matlab-master/klog.m | 1,320 | utf_8 | 2bcc976521eaa48ff1e83ec512f2c568 | %KLOG Laplacian of Gaussian kernel
%
% K = KLOG(SIGMA) is a 2-dimensional Laplacian of Gaussian kernel of
% width (standard deviation) SIGMA and centred within the matrix K whose
% half-width is H=3xSIGMA, and W=2xH+1.
%
% K = KLOG(SIGMA, H) as above but the half-width H is specified.
%
% See also KGAUSS, KDOG, KDGAUS... |
github | petercorke/machinevision-toolbox-matlab-master | camcalt8.m | .m | machinevision-toolbox-matlab-master/camcalt8.m | 1,313 | utf_8 | eab3769babcaeb1c287b1596e2cb5cd8 | % optimization target function used by camcalt
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Fre... |
github | petercorke/machinevision-toolbox-matlab-master | xy2xyz.m | .m | machinevision-toolbox-matlab-master/xy2xyz.m | 941 | utf_8 | ddae79b0cac73c0f00a091d9ab9d867a |
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Foundation, either version 3 of the Li... |
github | petercorke/machinevision-toolbox-matlab-master | l2m.m | .m | machinevision-toolbox-matlab-master/l2m.m | 901 | utf_8 | 84ce56d3606ca0d390c419df8f891fcd | %L2M convert list to 2-column matrix
%
% m = l2m(list)
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% ... |
github | petercorke/machinevision-toolbox-matlab-master | morphdemo.m | .m | machinevision-toolbox-matlab-master/morphdemo.m | 3,516 | utf_8 | e2010c039c3a9aa32a3ce72411c79702 | %MORPHDEMO Demonstrate morphology using animation
%
% MORPHDEMO(IM, SE, OPTIONS) displays an animation to show the principles
% of the mathematical morphology operations dilation or erosion. Two
% windows are displayed side by side, input binary image on the left and
% output image on the right. The structuring eleme... |
github | petercorke/machinevision-toolbox-matlab-master | itrim.m | .m | machinevision-toolbox-matlab-master/itrim.m | 3,799 | utf_8 | 0218deaf895d8f9cff36cee8b406e725 | %ITRIM Trim images
%
% This function has two different modes of functionality.
%
% OUT = ITRIM(IM, SIDES, N) is the image IM with N pixels removed from the
% image sides as specified by SIDES which is a string containing one or
% more of the characters:
% 't' top
% 'b' bottom
% 'l' left
% 'r' right
%
%... |
github | petercorke/machinevision-toolbox-matlab-master | humoments.m | .m | machinevision-toolbox-matlab-master/humoments.m | 2,125 | utf_8 | 8de2ad93de5b99c31e07d4f7b7809a03 | %HUMOMENTS Hu moments
%
% PHI = HUMOMENTS(IM) is the vector (1x7) of Hu moment invariants for the binary
% image IM.
%
% Notes::
% - IM is assumed to be a binary image of a single connected region
%
% Reference::
% M-K. Hu,
% Visual pattern recognition by moment invariants.
% IRE Trans. on Information Theory, IT-8:pp... |
github | petercorke/machinevision-toolbox-matlab-master | zsad.m | .m | machinevision-toolbox-matlab-master/zsad.m | 1,340 | utf_8 | e8b8b0d173f7254ff8e6327f78e83f05 | %ZSAD Sum of absolute differences
%
% M = ZSAD(I1, I2) is the zero-mean sum of absolute differences between the
% two equally sized image patches I1 and I2. The result M is a scalar that
% indicates image similarity, a value of 0 indicates identical pixel patterns
% and is increasingly positive as image dissimilarity... |
github | petercorke/machinevision-toolbox-matlab-master | mksq.m | .m | machinevision-toolbox-matlab-master/mksq.m | 1,302 | utf_8 | bc7003bf039ce3b14c9758a3ceaaba1c | %MKSQ Make a test pattern comprising squares
%
% im = MKSQ(w, numsq)
%
% Create a square output image (W x W) with NUMSQ filled squares along
% the diagonal. Pixels in the squares are set to one, all others to zero.
%
% SEE ALSO: mkline, ihough, xyhough
%
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file ... |
github | petercorke/machinevision-toolbox-matlab-master | otsu.m | .m | machinevision-toolbox-matlab-master/otsu.m | 3,121 | utf_8 | 3e9424eee72bf779d135a43353eac23e | %OTSU Threshold selection
%
% T = OTSU(IM) is an optimal threshold for binarizing an image with a bimodal
% intensity histogram. T is a scalar threshold that maximizes the variance
% between the classes of pixels below and above the thresold T.
%
% Example::
% t = otsu(im);
% idisp(im >= t);
%
% Options::
% ... |
github | petercorke/machinevision-toolbox-matlab-master | houghshow.m | .m | machinevision-toolbox-matlab-master/houghshow.m | 1,009 | utf_8 | 968129fccafd251cdeefc256ab3f3fad | %HOUGHSHOW Show Hough accumulator
%
% houghshow(H)
%
% Displays the Hough accumulator as an image.
%
% SEE ALSO: ihough
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under th... |
github | petercorke/machinevision-toolbox-matlab-master | imeshgrid.m | .m | machinevision-toolbox-matlab-master/imeshgrid.m | 1,795 | utf_8 | 47adef7ce135acea7d8f8c0a03482bf0 | %IMESHGRID Domain matrices for image
%
% [U,V] = IMESHGRID(IM) are matrices that describe the domain of image IM (HxW)
% and are each HxW. These matrices are used for the evaluation of functions
% over the image. The element U(R,C) = C and V(R,C) = R.
%
% [U,V] = IMESHGRID(W, H) as above but the domain is WxH.
%
% [U... |
github | petercorke/machinevision-toolbox-matlab-master | iread.m | .m | machinevision-toolbox-matlab-master/iread.m | 14,808 | utf_8 | b9baefd78f302e7db887410131ff5b31 | %IREAD Read image from file
%
% IM = IREAD() presents a file selection GUI from which the user can select
% an image file which is returned as a matrix. On subsequent calls
% the initial folder is as set on the last call.
%
% IM = IREAD([], OPTIONS) as above but allows options to be specified.
%
% IM = IREAD(PATH, O... |
github | petercorke/machinevision-toolbox-matlab-master | RegionFeature.m | .m | machinevision-toolbox-matlab-master/RegionFeature.m | 16,494 | utf_8 | 586dbf0e1381b772fe6168ba813b0086 | %RegionFeature Region feature class
%
% This class represents a region feature.
%
% Methods::
% boundary Return the boundary as a list
% box Return the bounding box
% plot Plot the centroid
% plot_boundary Plot the boundary
% plot_box Plot the bounding box
% plot_ellipse Plot t... |
github | petercorke/machinevision-toolbox-matlab-master | upq.m | .m | machinevision-toolbox-matlab-master/upq.m | 1,207 | utf_8 | df7604f28dc2cb6d50dda498e03e7c4a | %UPQ Central image moments
%
% M = UPQ(IM, P, Q) is the PQ'th central moment of the image IM. That is,
% the sum of I(x,y).(x-x0)^P.(y-y0)^Q where (x0,y0) is the centroid.
%
% Notes::
% - The central moments are invariant to translation.
%
% See also UPQ_POLY, MPQ, NPQ.
% Copyright (C) 1993-2011, by Peter I. Corke
... |
github | petercorke/machinevision-toolbox-matlab-master | isize.m | .m | machinevision-toolbox-matlab-master/isize.m | 1,762 | utf_8 | 4d32cbcf2a6fb6d9e7bb5a1e6f47dc98 | %ISIZE Size of image
%
% N = ISIZE(IM,D) is the size of the D'th dimension of IM.
%
% [W,H] = ISIZE(IM) is the image width W and height H.
%
% WH = ISIZE(IM) is the image size WH = [W H].
%
% [W,H,P] = ISIZE(IM) is the image width W, height H and and number of
% planes P. Even if the image has only two dimensions P w... |
github | petercorke/machinevision-toolbox-matlab-master | isobel.m | .m | machinevision-toolbox-matlab-master/isobel.m | 2,549 | utf_8 | 3065588ce0b9b8985012d0915ff4a7ef | %ISOBEL Sobel edge detector
%
% OUT = ISOBEL(IM) is an edge image computed using the Sobel edge operator
% convolved with the image IM. This is the norm of the vertical and horizontal
% gradients at each pixel. The Sobel horizontal gradient kernel is:
% 1 |1 0 -1|
% --- |2 0 -2|
% 8 |1 ... |
github | petercorke/machinevision-toolbox-matlab-master | hitormiss.m | .m | machinevision-toolbox-matlab-master/hitormiss.m | 1,349 | utf_8 | a96ce39936e47c0f299dba051a61f373 | %HITORMISS Hit or miss transform
%
% H = HITORMISS(IM, SE) is the hit-or-miss transform of the binary image IM with
% the structuring element SE. Unlike standard morphological operations S has
% three possible values: 0, 1 and don't care (represented by NaN).
%
% References::
% - Robotics, Vision & Control, Section 1... |
github | petercorke/machinevision-toolbox-matlab-master | homwarp.m | .m | machinevision-toolbox-matlab-master/homwarp.m | 4,578 | utf_8 | f95cf09eee18ba0e941238c1da6431dd | %HOMWARP Warp image by an homography
%
% OUT = HOMWARP(H, IM, OPTIONS) is a warp of the image IM obtained by
% applying the homography H to the coordinates of every input pixel.
%
% [OUT,OFFS] = HOMWARP(H, IM, OPTIONS) as above but OFFS is the offset of the
% warped tile OUT with respect to the origin of IM.
%
% Optio... |
github | petercorke/machinevision-toolbox-matlab-master | ipad.m | .m | machinevision-toolbox-matlab-master/ipad.m | 2,178 | utf_8 | 0aa87e13e1ab6da610d4537d521f4f47 | %IPAD Pad an image with constants
%
% OUT = IPAD(IM, SIDES, N) is a padded version of the image IM with a block
% of NaN values N pixels wide on the sides of IM as specified by SIDES.
%
% OUT = IPAD(IM, SIDES, N, V) as above but pads with pixels of value V.
%
% SIDES is a string containing one or more of the character... |
github | petercorke/machinevision-toolbox-matlab-master | isimilarity.m | .m | machinevision-toolbox-matlab-master/isimilarity.m | 3,351 | utf_8 | 38fbc46ee08e9c5acda9b00e5e43466d | %ISIMILARITY Locate template in image
%
% S = ISIMILARITY(T, IM) is an image where each pixel is the ZNCC similarity
% of the template T (MxM) to the MxM neighbourhood surrounding the
% corresonding input pixel in IM. S is same size as IM.
%
% S = ISIMILARITY(T, IM, METRIC) as above but the similarity metric is specif... |
github | petercorke/machinevision-toolbox-matlab-master | idecimate.m | .m | machinevision-toolbox-matlab-master/idecimate.m | 1,832 | utf_8 | e72dcda62d44b7c16ac59134f30f7dcd | %IDECIMATE Decimate an image
%
% S = IDECIMATE(IM, M) is a decimated version of the image IM whose
% size is reduced by M (an integer) in both dimensions. The image is smoothed
% with a Gaussian kernel with standard deviation M/2 then subsampled.
%
% S = IDECIMATE(IM, M, SD) as above but the standard deviation of the
... |
github | petercorke/machinevision-toolbox-matlab-master | yuvclose.m | .m | machinevision-toolbox-matlab-master/yuvclose.m | 874 | utf_8 | 26a4c1a229a5e74974000dcc08e92711 | %YUVCLOSE Close a YUV4MPEG file
%
% yuvclose(yuv)
%
% Close an open YUV file.
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public Lic... |
github | petercorke/machinevision-toolbox-matlab-master | dtransform.m | .m | machinevision-toolbox-matlab-master/dtransform.m | 2,273 | utf_8 | 5ece98660b9f901b8aaca09bf1ae38c5 | %DTRANSFORM Distance transform
%
% DT = DTRANSFORM(IM, OPTIONS) is the distance transform of the
% binary image IM. The value of each output pixel is the distance (pixels)
% to the closest set pixel.
%
% Options::
% 'Euclidean' use Euclidean distance (default)
% 'cityblock' use cityblock (Manhattan) distance
% 'sh... |
github | petercorke/machinevision-toolbox-matlab-master | circle.m | .m | machinevision-toolbox-matlab-master/circle.m | 894 | utf_8 | 6cc0c9330d9be6c4e25353db86dfb98a |
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Foundation, either version 3 of the Li... |
github | petercorke/machinevision-toolbox-matlab-master | loadppm.m | .m | machinevision-toolbox-matlab-master/loadppm.m | 4,012 | utf_8 | 466270171b72f02aacdba4486c8d0fbf | %LOADPPM Load a PPM image
%
% I = loadppm(filename)
% I = loadppm(filename, n)
%
% Returns a matrix containing the image loaded from the PPM format
% file filename. Handles ASCII (P3) and binary (P6) PGM file formats.
% Result is returned as a 3 dimensional array where the last index
% is the color plane.
%
% If the f... |
github | petercorke/machinevision-toolbox-matlab-master | saveinr.m | .m | machinevision-toolbox-matlab-master/saveinr.m | 1,614 | utf_8 | 078bd0cd4458025d7b529f3135cee8cc | %SAVEINR Write an INRIMAGE format file
%
% SAVEINR(filename, im)
%
% Saves the specified image array in a INRIA image format file.
%
% SEE ALSO: loadinr
%
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribu... |
github | petercorke/machinevision-toolbox-matlab-master | zncc.m | .m | machinevision-toolbox-matlab-master/zncc.m | 1,419 | utf_8 | 6e1b01702555e6a2540868b39383f0ba | %ZNCC Normalized cross correlation
%
% M = ZNCC(I1, I2) is the zero-mean normalized cross-correlation between the
% two equally sized image patches I1 and I2. The result M is a scalar in
% the interval -1 to 1 that indicates similarity. A value of 1 indicates
% identical pixel patterns.
%
% Notes::
% - The ZNCC si... |
github | petercorke/machinevision-toolbox-matlab-master | invcamcal.m | .m | machinevision-toolbox-matlab-master/invcamcal.m | 2,279 | utf_8 | 17e1bc99ac466be3e2b230b2d4ed6069 | %INVCAMCAL Inverse camera calibration
%
% c = INVCAMCAL(C)
%
% Decompose, or invert, a 3x4camera calibration matrix C.
% The result is a camera object with the following parameters set:
% f
% sx, sy (with sx=1)
% (u0, v0) principal point
% Tcam is the homog xform of the world origin wrt camera
%
... |
github | petercorke/machinevision-toolbox-matlab-master | ilogpolar.m | .m | machinevision-toolbox-matlab-master/ilogpolar.m | 2,196 | utf_8 | 9c9e6c2dba70640b07564ee6cde3342c | %ILOGPOLAR Log-polar transform
%
% OUT = ILOGPOLAR(IM, OPTIONS) is a log-polar representation of the
% image IM. Every pixel in IM is rendered at the coordinate (log(r), theta)
% in the output image OUT (WxH), and where (r,theta) is the polar coordinate
% of the correspondingin pixel in the image IM.
%
% [OUT,VTH,VLO... |
github | petercorke/machinevision-toolbox-matlab-master | campose4.m | .m | machinevision-toolbox-matlab-master/campose4.m | 2,944 | utf_8 | bdafb375e5b25cd76eead0821cc3bb4e | %CAMPOSE4 Camera pose estimation from 4 coplanar points.
%
% T = CAMPOSE4(D, ci)
% [T, UV0] = CAMPOSE4(D, ci)
%
% Input is a table of data points, D, with each row of the form [X Y u v]
% where (X, Y) are the world coordinate of the planar points with respect
% to some coordinate system whose origin lies within the pla... |
github | petercorke/machinevision-toolbox-matlab-master | homog_solve.m | .m | machinevision-toolbox-matlab-master/homog_solve.m | 3,556 | utf_8 | f3b924134840d4d291c398346d01baae | %HOMOG_SOLVE various linear equation solvers used by fmatrix and homography
%
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public Lic... |
github | petercorke/machinevision-toolbox-matlab-master | oflow.m | .m | machinevision-toolbox-matlab-master/oflow.m | 2,118 | utf_8 | c765873685994e0859e40fe055979b39 | %OFLOW simple optical flow based on corner correspondance
%
% oflow(c1, c2)
% oflow(c1, c2, w)
% oflow(c1, c2, w, thresh)
%
% c1, c2 are corner structures from showcorners(). Perform exhaustive
% cross matching between the two sets of corners using ZNCC similarity
% measure. Takes first 100 corners.
%
% w is the matc... |
github | petercorke/machinevision-toolbox-matlab-master | ksobel.m | .m | machinevision-toolbox-matlab-master/ksobel.m | 1,136 | utf_8 | 30cb3d1840c523c7a2d1a559713a2193 | %KSOBEL Sobel edge detector
%
% K = KSOBEL() is the Sobel x-derivative kernel:
% 1/8 |1 0 -1|
% |2 0 -2|
% |1 0 -1|
%
% Notes::
% - This kernel is an effective vertical-edge detector
% - The y-derivative (horizontal-edge) kernel is K'
%
% See also ISOBEL.
% Copyright (C) 1993... |
github | petercorke/machinevision-toolbox-matlab-master | xyz2xy.m | .m | machinevision-toolbox-matlab-master/xyz2xy.m | 925 | utf_8 | 8222b4effca0967a742cdb796fb97c74 |
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Foundation, either version 3 of the Li... |
github | petercorke/machinevision-toolbox-matlab-master | homline.m | .m | machinevision-toolbox-matlab-master/homline.m | 940 | utf_8 | 36f8bfc6e4857581a153ab19866f45a9 |
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% MVTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Foundation, either version 3 of the Li... |
github | petercorke/machinevision-toolbox-matlab-master | klaplace.m | .m | machinevision-toolbox-matlab-master/klaplace.m | 1,044 | utf_8 | 47fb4e2321008032531ebeb60eebeefd | %KLAPLACE Laplacian kernel
%
% K = KLAPLACE() is the Laplacian kernel:
% |0 1 0|
% |1 -4 1|
% |0 1 0|
%
% Notes::
% - This kernel has an isotropic response to image gradient.
%
% See also ILAPLACE, ICONV.
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine V... |
github | petercorke/machinevision-toolbox-matlab-master | sad.m | .m | machinevision-toolbox-matlab-master/sad.m | 1,180 | utf_8 | d2607212bcb5fd31eff9e88951350421 | %SAD Sum of absolute differences
%
% M = SAD(I1, I2) is the sum of absolute differences between the
% two equally sized image patches I1 and I2. The result M is a scalar that
% indicates image similarity, a value of 0 indicates identical pixel patterns
% and is increasingly positive as image dissimilarity increases.
... |
github | petercorke/machinevision-toolbox-matlab-master | zcross.m | .m | machinevision-toolbox-matlab-master/zcross.m | 1,526 | utf_8 | 01ac2587938315294ddf1b848f8fa6cd | %ZCROSS Zero-crossing detector
%
% IZ = ZCROSS(IM) is a binary image with pixels set where the corresponding
% pixels in the signed image IM have a zero crossing, a positive pixel
% adjacent to a negative pixel.
%
% Notes::
% - Can be used in association with a Lapalacian of Gaussian image to
% determine edges.
%
... |
github | petercorke/machinevision-toolbox-matlab-master | iprocrustes.m | .m | machinevision-toolbox-matlab-master/iprocrustes.m | 1,507 | utf_8 | 75981b4204d09d1de46a0bd61754cd80 | %IPROCRUSTES Point cloud alignment
%
% T = IPROCRUSTES(P1, P2) is the transform that best transforms point set
% P1 (3xN) to P2 (3xN). Point correspondence is assumed to be known, that is,
% the Ith column of P1 corresponds to the Ith column of P2.
%
% [T,S] = IPROCRUSTES(P1, P2) as above but also returns the overall ... |
github | petercorke/machinevision-toolbox-matlab-master | imser.m | .m | machinevision-toolbox-matlab-master/imser.m | 3,896 | utf_8 | af07a5409d6531743e5e462ee6f44d00 | %IMSER Maximally stable extremal regions
%
% LABEL = IMSER(IM, OPTIONS) is a segmentation of the greyscale image IM (HxW)
% based on maximally stable extremal regions. LABEL (HxW) is an image where
% each element is the integer label assigned to the corresponding pixel in IM.
% The labels are consecutive integers sta... |
github | petercorke/machinevision-toolbox-matlab-master | isurf.m | .m | machinevision-toolbox-matlab-master/isurf.m | 6,101 | utf_8 | 10838c3894f573cdbf725b9c0f978524 | %ISURF SURF feature extractor
%
% SF = ISURF(IM, OPTIONS) returns a vector of SurfPointFeature objects
% representing scale and rotationally invariant interest points in the
% image IM.
%
% The SurfPointFeature object has many properties including:
% u horizontal coordinate
% v vertical coordina... |
github | petercorke/machinevision-toolbox-matlab-master | ithresh.m | .m | machinevision-toolbox-matlab-master/ithresh.m | 5,384 | utf_8 | e6d9d6ea14cb86491d14aac6940162ff | %ITHRESH Interactive image threshold
%
% ITHRESH(IM) displays the image IM in a window with a slider which
% adjusts the binary threshold.
%
% ITHRESH(IM, T) as above but the initial threshold is set to T.
%
% IM2 = ITHRESH(IM) as above but returns the thresholded image after the
% "done" button in the GUI is pressed.
... |
github | petercorke/machinevision-toolbox-matlab-master | istretch.m | .m | machinevision-toolbox-matlab-master/istretch.m | 1,699 | utf_8 | 3f85d3888ea31525c61ec7357482be94 | %ISTRETCH Image normalization
%
% OUT = ISTRETCH(IM, OPTIONS) is a normalized image in which all pixel
% values lie in the range 0 to 1. That is, a linear mapping where the
% minimum value of IM is mapped to 0 and the maximum value of IM is
% mapped to 1.
%
% Options::
% 'max',M Pixels are mapped to the range 0... |
github | petercorke/machinevision-toolbox-matlab-master | camcalt.m | .m | machinevision-toolbox-matlab-master/camcalt.m | 4,465 | utf_8 | ac7ee26738ef5d310532c709c1c986bc | %CAMCALT Camera calibration using Tsai's two-stage method.
%
% This method works when the calibration target comprises coplanar points.
%
% [Tcam, f, k1]] = CAMCALT(D, PAR)
%
% Compute a 3x4 camera calibration matrix from calibration data
% using the method of Tsai.
%
% D is camera calibration data with rows of the f... |
github | petercorke/machinevision-toolbox-matlab-master | irectify.m | .m | machinevision-toolbox-matlab-master/irectify.m | 8,328 | utf_8 | 23f77d39443f6a31f0ab2acefe684f5f | %IRECTIFY Rectify stereo image pair
%
% [OUT1,OUT2] = IRECTIFY(F, M, IM1, IM2) is a rectified pair of images
% corresponding to IM1 and IM2. F (3x3) is the fundamental matrix relating
% the two views and M is a FeatureMatch object containing point correspondences
% between the images.
%
% [OUT1,OUT2,H1,H2] = IRECTIF... |
github | petercorke/machinevision-toolbox-matlab-master | iint.m | .m | machinevision-toolbox-matlab-master/iint.m | 2,475 | utf_8 | d10080710ff49b730dcfad7e31d4b0ab | %IINT Convert image to integer class
%
% OUT = IINT(IM) is an image with unsigned 8-bit integer elements in the
% range 0 to 255 corresponding to the elements of the image IM.
%
% OUT = IINT(IM, CLASS) as above but the output pixels belong to the
% integer class CLASS.
%
% Examples::
% Convert double precision image... |
github | petercorke/machinevision-toolbox-matlab-master | ipyramid.m | .m | machinevision-toolbox-matlab-master/ipyramid.m | 1,925 | utf_8 | c2b423b0fed42d0b5f8ae1f905c0547e | %IPYRAMID Pyramidal image decomposition
%
% OUT = IPYRAMID(IM) is a pyramid decomposition of input image IM using
% Gaussian smoothing with standard deviation of 1. OUT is a cell array of
% images each one having dimensions half that of the previous image. The
% pyramid is computed down to a non-halvable image size.... |
github | petercorke/machinevision-toolbox-matlab-master | icp.m | .m | machinevision-toolbox-matlab-master/icp.m | 7,829 | utf_8 | 10c747c2c3114c9ebf415f4f5cd2e923 | %ICP Point cloud alignment
%
% T = ICP(P1, P2, OPTIONS) is the homogeneous transformation that best
% transforms the set of points P1 to P2 using the iterative closest point
% algorithm.
%
% [T,D] = ICP(P1, P2, OPTIONS) as above but also returns the norm of the
% error between the transformed point set P2 and P1.
%
% O... |
github | petercorke/machinevision-toolbox-matlab-master | ireplicate.m | .m | machinevision-toolbox-matlab-master/ireplicate.m | 1,534 | utf_8 | eb5354d987333eab3fc968979f0a5df5 | %IREPLICATE Expand image
%
% OUT = IREPLICATE(IM, K) is an expanded version of the image (HxW) where
% each pixel is replicated into a KxK tile. If IM is HxW the result is (KH)x(KW).
%
% See also IDECIMATE, ISCALE.
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for... |
github | petercorke/machinevision-toolbox-matlab-master | fmatrix.m | .m | machinevision-toolbox-matlab-master/fmatrix.m | 7,921 | utf_8 | 73543003e55f79be01ca40675c0b485d | %FMATRIX Estimate fundamental matrix
%
% F = FMATRIX(P1, P2, OPTIONS) is the fundamental matrix (3x3) that
% relates two sets of corresponding points P1 (2xN) and P2 (2xN) from
% two different camera views.
%
% Notes::
% - The points must be corresponding, no outlier rejection is performed.
% - Contains a RANSAC driver... |
github | petercorke/machinevision-toolbox-matlab-master | ierode.m | .m | machinevision-toolbox-matlab-master/ierode.m | 2,422 | utf_8 | cbb97f364517e667ccf6d1f4ea7e9a0f | %IERODE Morphological erosion
%
% OUT = IERODE(IM, SE, OPTIONS) is the image IM after morphological erosion
% with the structuring element SE.
%
% OUT = IERODE(IM, SE, N, OPTIONS) as above but the structuring element
% SE is applied N times, that is N erosions.
%
% Options::
% 'border' the border value is replicated... |
github | petercorke/machinevision-toolbox-matlab-master | idilate.m | .m | machinevision-toolbox-matlab-master/idilate.m | 2,435 | utf_8 | 628fb9cd408d5d13f436314ebccce066 | %IDILATE Morphological dilation
%
% OUT = IDILATE(IM, SE, OPTIONS) is the image IM after morphological dilation
% with the structuring element SE.
%
% OUT = IDILATE(IM, SE, N, OPTIONS) as above but the structuring element
% SE is applied N times, that is N dilations.
%
% Options::
% 'border' the border value is rep... |
github | petercorke/machinevision-toolbox-matlab-master | peak.m | .m | machinevision-toolbox-matlab-master/peak.m | 4,673 | utf_8 | d8ce4d306e15199d67742ed68a63dd20 | %PEAK Find peaks in vector
%
% YP = PEAK(Y, OPTIONS) are the values of the maxima in the vector Y.
%
% [YP,I] = PEAK(Y, OPTIONS) as above but also returns the indices of the maxima
% in the vector Y.
%
% [YP,XP] = PEAK(Y, X, OPTIONS) as above but also returns the corresponding
% x-coordinates of the maxima in the vect... |
github | petercorke/machinevision-toolbox-matlab-master | igraphseg.m | .m | machinevision-toolbox-matlab-master/igraphseg.m | 2,026 | utf_8 | 1c089afe5e93e98f36b3d808108fe062 | %IGRAPHSEG Graph-based image segmentation
%
% L = IGRAPHSEG(IM, K, MIN) is a graph-based segmentation of the color
% image IM (HxWx3). L (HxW) is an image where each element is the label
% assigned to the corresponding pixel in IM. K is the scale parameter,
% and a larger value indicates a preference for larger re... |
github | petercorke/machinevision-toolbox-matlab-master | rgb2xyz.m | .m | machinevision-toolbox-matlab-master/rgb2xyz.m | 1,553 | utf_8 | 0dff68180e1358b4de84476ac646e147 | %RGB2XYZ Convert RGB to XYZ color space
%
% [x, y, z] = RGB2XYZ(r, g, b)
% xyz = RGB2XYZ(rgb)
%
% Convert (R,G,B) coordinates to (X,Y,Z) color space.
% If RGB (or R, G, B) have more than one row, then computation is
% done row wise.
%
% SEE ALSO: ccxyz cmfxyz
%
% Copyright (C) 1995-2009, by Peter I. Corke
%
% This fi... |
github | petercorke/machinevision-toolbox-matlab-master | homography.m | .m | machinevision-toolbox-matlab-master/homography.m | 9,087 | utf_8 | 0910b2de725c03a3879431ac284a5baf | %HOMOGRAPHY Estimate homography
%
% H = HOMOGRAPHY(P1, P2) is the homography (3x3) that relates two
% sets of corresponding points P1 (2xN) and P2 (2xN) from two different
% camera views of a planar object.
%
% Notes::
% - The points must be corresponding, no outlier rejection is performed.
% - The points must be proje... |
github | petercorke/machinevision-toolbox-matlab-master | istereo.m | .m | machinevision-toolbox-matlab-master/istereo.m | 7,347 | utf_8 | a0f567d87cf0804cd5427200f806fb51 | %ISTEREO Stereo matching
%
% D = ISTEREO(LEFT, RIGHT, RANGE, H, OPTIONS) is a disparity image computed
% from the epipolar aligned stereo pair: the left image LEFT (HxW) and the
% right image RIGHT (HxW). D (HxW) is the disparity and the value at each
% pixel is the horizontal shift of the corresponding pixel in IML ... |
github | petercorke/machinevision-toolbox-matlab-master | mpq_point.m | .m | machinevision-toolbox-matlab-master/mpq_point.m | 1,062 | utf_8 | bc1df4bba361b173110c0281a977f2da | %MPQ Compute moments of image points
%
% M = MPQ(POINTS, P, Q) is the PQ'th moment of the set of points POINTS.
% That is, the sum of x^P y^Q where (x,y) are the rows of POINTS.
%
% See also MPQ.
% Copyright (C) 1993-2011, by Peter I. Corke
%
% This file is part of The Machine Vision Toolbox for Matlab (MVTB).
%
% M... |
github | petercorke/machinevision-toolbox-matlab-master | lambda2rg.m | .m | machinevision-toolbox-matlab-master/lambda2rg.m | 1,649 | utf_8 | 8fe48ea2d08fbf217cab276fe33834d3 | %LAMBDA2RGB RGB chromaticity coordinates
%
% RGB = LAMBDA2RG(LAMBDA) is the rg-chromaticity coordinate (1x2) for
% illumination at the specific wavelength LAMBDA [m]. If LAMBDA is a
% vector (Nx1), then P (Nx2) is a vector whose elements are the chromaticity
% coordinates at the corresponding elements of LAMBDA.
%
% R... |
github | petercorke/machinevision-toolbox-matlab-master | iline.m | .m | machinevision-toolbox-matlab-master/iline.m | 1,443 | utf_8 | 4f4a13cf78820768ac4a0026158f18d3 | %ILINE Draw a line in an image
%
% OUT = ILINE(IM, P1, P2) is a copy of the image IM with a single-pixel thick
% line drawn between the points P1 and P2, each a 2-vector [U,V]. The pixels
% on the line are set to 1.
%
% OUT = ILINE(IM, P1, P2, V) as above but the pixels on the line are set to V.
%
% Notes::
% - Uses ... |
github | petercorke/machinevision-toolbox-matlab-master | showcolorspace.m | .m | machinevision-toolbox-matlab-master/showcolorspace.m | 4,293 | utf_8 | c990e3ac43f633ae5a6b6efe0badfaf1 | %SHOWCOLORSPACE Display spectral locus
%
% SHOWCOLORSPACE('xy') display a fully colored spectral locus in terms of CIE x and y
% coordinates.
%
% SHOWCOLORSPACE('Lab') display a fully colored spectral locus in terms of CIE L*a*b*
% coordinates.
%
% SHOWCOLORSPACE(WHICH, P) as above but plot the points whose xy- or a*... |
github | petercorke/machinevision-toolbox-matlab-master | ithin.m | .m | machinevision-toolbox-matlab-master/ithin.m | 1,870 | utf_8 | 8b1f2b845224a0361f6b293ac093b6f1 | %ITHIN Morphological skeletonization
%
% OUT = ITHIN(IM) is the binary skeleton of the binary image IM. Any non-zero
% region is replaced by a network of single-pixel wide lines.
%
% OUT = ITHIN(IM,DELAY) as above but graphically displays each iteration
% of the skeletonization algorithm with a pause of DELAY second... |
github | petercorke/machinevision-toolbox-matlab-master | blackbody.m | .m | machinevision-toolbox-matlab-master/blackbody.m | 1,620 | utf_8 | fa7a6a1690e4c7b0f29d56455bcbfcd9 | %BLACKBODY Compute blackbody emission spectrum
%
% E = BLACKBODY(LAMBDA, T) is the blackbody radiation power density [W/m^3]
% at the wavelength LAMBDA [m] and temperature T [K].
%
% If LAMBDA is a column vector (Nx1), then E is a column vector (Nx1) of
% blackbody radiation power density at the corresponding elements ... |
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