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github | brennanyama/robotx-master | niblack.m | .m | robotx-master/pathplanning/Version_02/vision/niblack.m | 2,299 | utf_8 | daf8228a65e78fd0a74e07e411f1866f | %NIBLACK Adaptive thresholding
%
% T = NIBLACK(IM, K, W2) is the per-pixel (local) threshold to apply to
% image IM. T has the same dimensions as IM. The threshold at each pixel is
% a function of the mean and standard deviation computed over a WxW window,
% where W=2*w2+1.
%
% [T,M,S] = NIBLACK(IM, K, W2) as above... |
github | brennanyama/robotx-master | idisplabel.m | .m | robotx-master/pathplanning/Version_02/vision/idisplabel.m | 1,603 | utf_8 | fd08a9852e1a994a43b08388c4085729 | %IDISPLABEL Display an image with mask
%
% IDISPLABEL(IM, LABELIMAGE, LABELS) displays only those image pixels which
% belong to a specific class. IM is a greyscale (HxW) or color (HxWx3) image,
% and LABELIMAGE (HxW) contains integer pixel class labels for the
% corresponding pixels in IM. The pixel classes to be... |
github | brennanyama/robotx-master | luminos.m | .m | robotx-master/pathplanning/Version_02/vision/luminos.m | 4,447 | utf_8 | 1954b09e77ca9eed2544187c928428f6 | %LUMINOS Photopic luminosity function
%
% P = LUMINOS(LAMBDA) is the photopic luminosity function for the wavelengths
% in LAMBDA [m]. If LAMBDA is a vector (Nx1), then P (Nx1) is a vector whose
% elements are the luminosity at the corresponding elements of LAMBDA.
%
% Luminosity has units of lumens which are the int... |
github | brennanyama/robotx-master | idouble.m | .m | robotx-master/pathplanning/Version_02/vision/idouble.m | 1,794 | utf_8 | 6fdab554ff4a1c704b333f74af3326ad | %IDOUBLE Convert integer image to double
%
% IMD = IDOUBLE(IM) is an image with double precision elements in the
% range 0 to 1 corresponding to the elements of IM. The integer pixels IM
% are assumed to span the range 0 to the maximum value of their integer class.
%
% Notes::
% - Works for an image with arbitrary numb... |
github | brennanyama/robotx-master | ipaste.m | .m | robotx-master/pathplanning/Version_02/vision/ipaste.m | 2,693 | utf_8 | 873289eba5eed3d4448ac98d47b62727 | %IPASTE Paste an image into an image
%
% OUT = IPASTE(IM, IM2, P, OPTIONS) is the image IM with the subimage IM2
% pasted in at the position P=[U,V].
%
% Options::
% 'centre' The pasted image is centred at P, otherwise P is the top-left
% corner of the subimage in IM (default)
% 'zero' the coordinate... |
github | brennanyama/robotx-master | iconcat.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | colorspace.m | .m | robotx-master/pathplanning/Version_02/vision/colorspace.m | 13,716 | utf_8 | 4df66ccb3b2b8252e0a79128786a4d43 | %COLORSPACE Color space conversion of image
%
% OUT = COLORSPACE(S, IM) converts the image IM to a different color
% space according to the string S which specifies the source and destination
% color spaces, S = 'dest<-src', or alternatively, S = 'src->dest'. Input
% and output images have 3 planes.
%
% [O1,O2,O3] =... |
github | brennanyama/robotx-master | iendpoint.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | isift.m | .m | robotx-master/pathplanning/Version_02/vision/isift.m | 5,239 | utf_8 | 1c3ec9d8024e0bf8f9d54cd2a36593e1 | %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 (default 0)
%... |
github | brennanyama/robotx-master | isamesize.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | iconv.m | .m | robotx-master/pathplanning/Version_02/vision/iconv.m | 2,119 | utf_8 | 4822c224cb1bc13c378432a0bdacdd9b | %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 | brennanyama/robotx-master | icanny.m | .m | robotx-master/pathplanning/Version_02/vision/icanny.m | 2,501 | utf_8 | 10ac73562890ae30eda14f7800fbfd85 | %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 standar... |
github | brennanyama/robotx-master | ccxyz.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | h2e.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | icolor.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | iscalemax.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | irotate.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | ismooth.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | inormhist.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | itriplepoint.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | iblobs.m | .m | robotx-master/pathplanning/Version_02/vision/iblobs.m | 6,434 | utf_8 | 5334656be7643c20ab1c1cf2fa78d0e8 | %IBLOBS Blob features
%
% F = IBLOBS(IM, OPTIONS) is a vector of RegionFeature objects that
% describe each connected region in the image IM.
%
% Options::
% 'aspect',A set pixel aspect ratio, default 1.0
% 'connect',C set connectivity, 4 (default) or 8
% 'greyscale' compute greyscale moments 0 (def... |
github | brennanyama/robotx-master | colorkmeans.m | .m | robotx-master/pathplanning/Version_02/vision/colorkmeans.m | 3,857 | utf_8 | cab9ecc62daba2e0f20afc9654d5cccf | %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 | brennanyama/robotx-master | ipixswitch.m | .m | robotx-master/pathplanning/Version_02/vision/ipixswitch.m | 4,352 | utf_8 | 40fad79cd30e34bc883f300145f2135e | %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 | brennanyama/robotx-master | mpq.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | upq_poly.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | ccdresponse.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | klog.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | morphdemo.m | .m | robotx-master/pathplanning/Version_02/vision/morphdemo.m | 3,425 | utf_8 | 016922bb9bff0873ab8e7d898d7e00d5 | %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 | brennanyama/robotx-master | itrim.m | .m | robotx-master/pathplanning/Version_02/vision/itrim.m | 3,796 | utf_8 | 8f5b609126354885a564c89ec05ed405 | %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 | brennanyama/robotx-master | humoments.m | .m | robotx-master/pathplanning/Version_02/vision/humoments.m | 2,103 | utf_8 | 2518e5505dafeb43e8b73c56a0c14b05 | %HUMOMENTS Hu moments
%
% PHI = HUMOMENTS(IM) is the vector (7x1) 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 | brennanyama/robotx-master | zsad.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | otsu.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | xycolorspace.m | .m | robotx-master/pathplanning/Version_02/vision/xycolorspace.m | 3,076 | utf_8 | ea039a8d9f3728d7a8650e616cf80525 | %XYCOLORSPACE Display spectral locus
%
% XYCOLORSPACE() display a fully colored spectral locus in terms of CIE x and y
% coordinates.
%
% XYCOLORSPACE(P) as above but plot the points whose xy-chromaticity
% is given by the columns of P.
%
% [IM,AX,AY] = XYCOLORSPACE() as above returns the spectral locus as an
% image ... |
github | brennanyama/robotx-master | imeshgrid.m | .m | robotx-master/pathplanning/Version_02/vision/imeshgrid.m | 1,796 | utf_8 | f947ba06efe3a530d5b4d7d1c8a63075 | %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 | brennanyama/robotx-master | iread.m | .m | robotx-master/pathplanning/Version_02/vision/iread.m | 9,309 | utf_8 | 346f93c3a9c38222a2f9cabdeb344dbc | %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 | brennanyama/robotx-master | upq.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | isize.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | isobel.m | .m | robotx-master/pathplanning/Version_02/vision/isobel.m | 2,566 | utf_8 | 601b2e8a978e2aba0841e5c055ac605e | %ISOBEL Sobel edge detector
%
% OUT = ISOBEL(IM) is an edge image computed using the Sobel edge operator
% applied to the image IM. This is the norm of the vertical and horizontal
% gradients at each pixel. The Sobel horizontal gradient kernel is:
% | -1 0 1|
% | -2 0 2|
% | -1 0 1|
%
% an... |
github | brennanyama/robotx-master | hitormiss.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | homwarp.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | ipad.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | isimilarity.m | .m | robotx-master/pathplanning/Version_02/vision/isimilarity.m | 3,353 | utf_8 | 4c152d661ff561698457f694a454e469 | %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 | brennanyama/robotx-master | idecimate.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | dtransform.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | zncc.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | invcamcal.m | .m | robotx-master/pathplanning/Version_02/vision/invcamcal.m | 1,768 | utf_8 | 40c1ec0499d73e6c4710fe4272903fb6 | %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 | brennanyama/robotx-master | ksobel.m | .m | robotx-master/pathplanning/Version_02/vision/ksobel.m | 1,113 | utf_8 | 7ed5a7dadb86c6163febe26e4c0325cb | %KSOBEL Sobel edge detector
%
% K = KSOBEL() is the Sobel x-derivative kernel:
% |-1 0 1|
% |-2 0 2|
% |-1 0 1|
%
% Notes::
% - This kernel is an effective horizontal edge detector
% - The Sobel vertical derivative is K'
%
% See also ISOBEL.
% Copyright (C) 1993-2011, by Peter I. ... |
github | brennanyama/robotx-master | homline.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | klaplace.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | sad.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | zcross.m | .m | robotx-master/pathplanning/Version_02/vision/zcross.m | 1,516 | utf_8 | 7df02cf679e20969ef99156d9c46ae76 | %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 | brennanyama/robotx-master | imser.m | .m | robotx-master/pathplanning/Version_02/vision/imser.m | 3,354 | utf_8 | 2222e228e773f2a1862ca1856ac2242b | %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 | brennanyama/robotx-master | isurf.m | .m | robotx-master/pathplanning/Version_02/vision/isurf.m | 5,974 | utf_8 | b58354c09b714ae9f2859c3a1ef4dbdc | %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 | brennanyama/robotx-master | ithresh.m | .m | robotx-master/pathplanning/Version_02/vision/ithresh.m | 5,272 | utf_8 | f17707af6d2629bc879200be70066499 | %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 | brennanyama/robotx-master | istretch.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | irectify.m | .m | robotx-master/pathplanning/Version_02/vision/irectify.m | 8,328 | utf_8 | 0b83a7aced27ba0b8306282521949803 | %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 | brennanyama/robotx-master | iint.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | ipyramid.m | .m | robotx-master/pathplanning/Version_02/vision/ipyramid.m | 1,892 | utf_8 | 75f720a35fc0c1086a9c153483ef3b08 | %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 | brennanyama/robotx-master | icp.m | .m | robotx-master/pathplanning/Version_02/vision/icp.m | 7,562 | utf_8 | a788c0994b2ae4e5d992cf3d48a01a65 | %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 | brennanyama/robotx-master | ireplicate.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | fmatrix.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | ierode.m | .m | robotx-master/pathplanning/Version_02/vision/ierode.m | 2,091 | utf_8 | 315dd81ea3d53f6f232d6cd81ab800a7 | %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 | brennanyama/robotx-master | idilate.m | .m | robotx-master/pathplanning/Version_02/vision/idilate.m | 2,100 | utf_8 | b59ee004a8ca155d06d6797f806136fa | %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 | brennanyama/robotx-master | igraphseg.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | rgb2xyz.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | homography.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | istereo.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | lambda2rg.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | iline.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | ithin.m | .m | robotx-master/pathplanning/Version_02/vision/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 | brennanyama/robotx-master | blackbody.m | .m | robotx-master/pathplanning/Version_02/vision/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 ... |
github | brennanyama/robotx-master | cmfxyz.m | .m | robotx-master/pathplanning/Version_02/vision/cmfxyz.m | 13,181 | utf_8 | cd59fa42274e69082fb3539c42b6ae69 | %CMFXYZ Color matching function
%
% The color matching function is the XYZ tristimulus required to match a
% particular wavelength excitation.
%
% XYZ = CMFXYZ(LAMBDA) is the CIE XYZ color matching function (Nx3) for illumination
% at wavelength LAMBDA (Nx1) [m]. If LAMBDA is a vector then each row of XYZ
% is the co... |
github | brennanyama/robotx-master | ransac.m | .m | robotx-master/pathplanning/Version_02/vision/ransac.m | 9,760 | utf_8 | 13123baef709e6ac72dcf775edab1fe4 | %RANSAC Random sample and consensus
%
% M = RANSAC(FUNC, X, T, OPTIONS) is the RANSAC algorithm that robustly fits
% data X to the model represented by the function FUNC. RANSAC classifies
% Points that support the model as inliers and those that do not as outliers.
%
% X typically contains corresponding point data, ... |
github | brennanyama/robotx-master | pnmfilt.m | .m | robotx-master/pathplanning/Version_02/vision/pnmfilt.m | 2,265 | utf_8 | 3dc367b3f684848a0f5de953b5b15149 | %PNMFILT Pipe image through PNM utility
%
% OUT = PNMFILT(CMD) runs the external program given by the string CMD
% and the output (assumed to be PNM format) is returned as OUT.
%
% OUT = PNMFILT(CMD, IM) pipes the image IM through the external program
% given by the string CMD and the output is returned as OUT. The ex... |
github | brennanyama/robotx-master | testpattern.m | .m | robotx-master/pathplanning/Version_02/vision/testpattern.m | 4,919 | utf_8 | 92920acd303f2b19fc650d577db8219b | %TESTPATTERN Create test images
%
% IM = TESTPATTERN(TYPE, W, ARGS) creates a test pattern image. If W is a
% scalar the image is WxW else W(2)xW(1). The image is specified by the
% string TYPE and one or two (type specific) arguments:
%
% 'rampx' intensity ramp from 0 to 1 in the x-direction. ARGS is the number
... |
github | brennanyama/robotx-master | colorize.m | .m | robotx-master/pathplanning/Version_02/vision/colorize.m | 2,039 | utf_8 | 9cdaf7aaac226ee00734db6d86052770 | %COLORIZE Colorize a greyscale image
%
% OUT = COLORIZE(IM, MASK, COLOR) is a color image where each pixel in OUT
% is set to the corresponding element of the greyscale image IM or a specified
% COLOR according to whether the corresponding value of MASK is true or false
% respectively. The color is specified as a 3-v... |
github | brennanyama/robotx-master | loadspectrum.m | .m | robotx-master/pathplanning/Version_02/vision/loadspectrum.m | 1,655 | utf_8 | 82377498e5dad05dc49b9ebacff8ef3a | %LOADSPECTRUM Load spectrum data
%
% S = LOADSPECTRUM(LAMBDA, FILENAME) is spectral data (NxD) from file FILENAME
% interpolated to wavelengths [metres] specified in LAMBDA (Nx1). The
% spectral data can be scalar (D=1) or vector (D>1) valued.
%
% [S,LAMBDA] = LOADSPECTRUM(LAMBDA, FILENAME) as above but also returns ... |
github | brennanyama/robotx-master | cie_primaries.m | .m | robotx-master/pathplanning/Version_02/vision/cie_primaries.m | 982 | utf_8 | 0e77c64d0e1c45a3254891c942c65412 | %CIE_PRIMARIES Define CIE primary colors
%
% P = CIE_PRIMARIES() is a 3-vector with the wavelengths [m] of the
% CIE 1976 red, green and blue primaries respectively.
% 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 ... |
github | brennanyama/robotx-master | icorner.m | .m | robotx-master/pathplanning/Version_02/vision/icorner.m | 10,341 | utf_8 | dc50a29c15c77aef084e97a50593067a | %ICORNER Corner detector
%
% F = ICORNER(IM, OPTIONS) is a vector of PointFeature objects describing
% corner features detected in the image IM. This is a non-scale space detector
% and by default the Harris method is used but Shi-Tomasi and Noble are also
% supported.
%
% If IM is an image sequence a cell array of P... |
github | brennanyama/robotx-master | iprofile.m | .m | robotx-master/pathplanning/Version_02/vision/iprofile.m | 1,673 | utf_8 | 3c9ad0cd1405a9421eb1f70c57dee41c | %IPROFILE Extract pixels along a line
%
% V = IPROFILE(IM, P1, P2) is a vector of pixel values extracted from the
% image IM (HxWxP) between the points P1 (2x1) and P2 (2x1). V (NxP) has
% one row for each point along the line and the row is the pixel value
% which will be a vector for a multi-plane image.
%
% [P,UV... |
github | brennanyama/robotx-master | tristim2cc.m | .m | robotx-master/pathplanning/Version_02/vision/tristim2cc.m | 2,007 | utf_8 | 7dd2b665c324c9f832e4b8f4f21ebe2a | %TRISTIM Tristimulus to chromaticity coordinates
%
% CC = TRISTIM2CC(TRI) is the chromaticity coordinate (1x2) corresponding to the
% tristimulus TRI (1x3). If TRI is RGB then CC is rg, if TRI is XYZ then
% CC is xy. Multiple tristimulus values can be given as rows of TRI (Nx3)
% in which case the chromaticity coord... |
github | brennanyama/robotx-master | camcald.m | .m | robotx-master/pathplanning/Version_02/vision/camcald.m | 2,287 | utf_8 | 8848e0d80809bbb7599ab8594f7080e5 | % CAMCALD Camera calibration from data points
%
% C = CAMCALD(D) is the camera matrix (3x4) determined by least squares
% from corresponding world and image-plane points. D is a table
% of points with rows of the form [X Y Z U V] where (X,Y,Z) is the
% coordinate of a world point and [U,V] is the corresponding imag... |
github | brennanyama/robotx-master | showpixels.m | .m | robotx-master/pathplanning/Version_02/vision/showpixels.m | 2,731 | utf_8 | 1b5a113a1433f0205419878f7810a426 | %SHOWPIXELS Show low resolution image
%
% Displays a low resolution image in detail as a grid with colored lines
% between pixels and numeric display of pixel values at each pixel. Useful
% for illustrating principles in teaching.
%
% Options::
% 'fmt',F Format string (defaults to %d or %.2f depending on imag... |
github | brennanyama/robotx-master | anaglyph.m | .m | robotx-master/pathplanning/Version_02/vision/anaglyph.m | 3,425 | utf_8 | 5d663f0afb213da20789f4d7932a99e4 | %ANAGLYPH Convert stereo images to an anaglyph image
%
% A = ANAGLYPH(LEFT, RIGHT) is an anaglyph image where the two images of
% a stereo pair are combined into a single image by coding them in two
% different colors. By default the left image is red, and the right
% image is cyan.
%
% ANAGLYPH(LEFT, RIGHT) as abov... |
github | brennanyama/robotx-master | ihist.m | .m | robotx-master/pathplanning/Version_02/vision/ihist.m | 4,178 | utf_8 | 22abad06f4894e0a47de4c8571cffffe | %IHIST Image histogram
%
% IHIST(IM, OPTIONS) displays the image histogram. For an image with multiple
% planes the histogram of each plane is given in a separate subplot.
%
% H = IHIST(IM, OPTIONS) is the image histogram as a column vector. For
% an image with multiple planes H is a matrix with one column per image... |
github | brennanyama/robotx-master | im2col.m | .m | robotx-master/pathplanning/Version_02/vision/im2col.m | 1,758 | utf_8 | 26fb890b3f818af4cebfb26a764dfc37 | %IM2COL Convert an image to pixel per row format
%
% OUT = IM2COL(IM) is a matrix (NxP) where each row represents a single
% of the image IM (HxWxP). The pixels are in image column order (ie. column
% 1, column 2 etc) and there are N=WxH rows.
%
% OUT = IM2COL(IM, MASK) as above but only includes pixels if:
% - the co... |
github | brennanyama/robotx-master | rluminos.m | .m | robotx-master/pathplanning/Version_02/vision/rluminos.m | 1,446 | utf_8 | a1888fbb27996829f1c1975d5d4488e3 | %RLUMINOS Relative photopic luminosity function
%
% P = RLUMINOS(LAMBDA) is the relative photopic luminosity function for the
% wavelengths in LAMBDA [m]. If LAMBDA is a vector (Nx1), then P (Nx1) is a
% vector whose elements are the luminosity at the corresponding elements
% of LAMBDA.
%
% Relative luminosity lies ... |
github | brennanyama/robotx-master | colordistance.m | .m | robotx-master/pathplanning/Version_02/vision/colordistance.m | 1,737 | utf_8 | a7d24bb5f09ca566145fce8c61f2cd30 | %COLORDISTANCE Colorspace distance
%
% D = COLORDISTANCE(IM, RG) is the Euclidean distance on the rg-chromaticity
% plane from coordinate RG=[r,g] to every pixel in the color image IM. D is
% an image with the same dimensions as IM and the value of each pixel is
% the color space distance of the corresponding pixel... |
github | brennanyama/robotx-master | kmeans.m | .m | robotx-master/pathplanning/Version_02/vision/kmeans.m | 6,609 | utf_8 | cfa02bd1ab87e89eb5eeb751c93a457a | %KMEANS K-means clustering
%
% [L,C] = KMEANS(X, K, OPTIONS) is a K-means clustering of multi-dimensional
% data points X (DxN) where N is the number of points, and D is the dimension.
% The data is organized into K clusters based on Euclidean distance from cluster
% centres C (DxK). L is a vector (Nx1) whose elements... |
github | brennanyama/robotx-master | iscalespace.m | .m | robotx-master/pathplanning/Version_02/vision/iscalespace.m | 2,379 | utf_8 | c3c4ec0ad46cd3c03fe4404502f41912 | %ISCALESPACE Scale-space image sequence
%
% [G,L,S] = ISCALESPACE(IM, N, SIGMA) is a scale space image sequence of
% length N derived from IM (HxW). The standard deviation of the smoothing
% Gaussian is SIGMA. At each scale step the variance of the Gaussian increases
% by SIGMA^2. The first step in the sequence i... |
github | brennanyama/robotx-master | cmfrgb.m | .m | robotx-master/pathplanning/Version_02/vision/cmfrgb.m | 6,314 | utf_8 | e2bd60ed2e9d6e2071e0cb6b34f446f1 | %CMFRGB RGB color matching function
%
% The color matching function is the RGB tristimulus required to match a
% particular spectral excitation.
%
% RGB = CMFRGB(LAMBDA) is the CIE color matching function (Nx3) for illumination
% at wavelength LAMBDA (Nx1) [m]. If LAMBDA is a vector then each row of RGB
% is the colo... |
github | brennanyama/robotx-master | support.m | .m | robotx-master/pathplanning/Version_02/vision/@SurfPointFeature/support.m | 1,427 | utf_8 | b1281bf15eea69a8e69619f27a1aa20f | %SurfPointFeature.support Support region of feature
%
% OUT = F.support(IM, W) is an image of the support region of the
% feature F, extracted from the image IM in which the feature appears.
% The support region is scaled to WxW and rotated so that the feature's
% orientation axis is upward.
%
% OUT = F.support(IMAGES... |
github | brennanyama/robotx-master | plot_camera.m | .m | robotx-master/pathplanning/Version_02/vision/@Camera/plot_camera.m | 3,428 | utf_8 | bfe8a755bd504490e87bcea41b694c6c | %Camera.plot_camera Display camera icon in world view
%
% C.plot_camera(OPTIONS) draw a camera as a simple 3D model in the current
% figure.
%
% Options::
% 'Tcam',T Camera displayed in pose T (homogeneous transformation 4x4)
% 'scale',S Overall scale factor (default 0.2 x maximum axis dimension)
% 'color',C ... |
github | brennanyama/robotx-master | iblobs.m | .m | robotx-master/pathplanning/Version_02/vision/IPT/iblobs.m | 7,626 | utf_8 | 06cfc1f9864723d5979db8b53a74319d | %IBLOBS Blob features
%
% F = IBLOBS(IM, OPTIONS) is a vector of RegionFeature objects that
% describe each connected region in the image IM.
%
% Options::
% 'aspect',A set pixel aspect ratio, default 1.0
% 'connect',C set connectivity, 4 (default) or 8
% 'greyscale' compute greyscale moments 0 (def... |
github | brennanyama/robotx-master | ierode.m | .m | robotx-master/pathplanning/Version_02/vision/IPT/ierode.m | 2,072 | utf_8 | 2d0b89d1378ddd50df74706987d94fab | %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 | brennanyama/robotx-master | idilate.m | .m | robotx-master/pathplanning/Version_02/vision/IPT/idilate.m | 2,082 | utf_8 | 356a1601fdd4d99915f30bf69b88cf77 | %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 | brennanyama/robotx-master | ilabeltest.m | .m | robotx-master/pathplanning/Version_02/vision/examples/ilabeltest.m | 981 | utf_8 | 43dea1022e496ffe77d1e9901b730c45 |
% Copyright (C) 1995-2009, 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 Lic... |
github | brennanyama/robotx-master | sphere_rotate.m | .m | robotx-master/pathplanning/Version_02/vision/examples/sphere_rotate.m | 2,063 | utf_8 | b378b89be34e3e55649e5a5b7e3862d1 |
% 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 | brennanyama/robotx-master | sphere_paint.m | .m | robotx-master/pathplanning/Version_02/vision/examples/sphere_paint.m | 1,334 | utf_8 | f11ed5a3015a59e90b75506740711238 |
% 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 | brennanyama/robotx-master | support.m | .m | robotx-master/pathplanning/Version_02/vision/@SiftPointFeature/support.m | 1,352 | utf_8 | 84c515e52432cf3f7a7a590758268add | %SiftPointFeature.support Support region of feature
%
% OUT = F.support(IM, W) is an image of the support region of the
% feature F, extracted from the image IM in which the feature appears.
% The support region is scaled to WxW and rotated so that the feature's
% orientation axis is upward.
%
% OUT = F.support(IMAGES... |
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