| from PIL import Image |
| import numpy as np |
| from scipy.fftpack import dct, idct |
| import io |
|
|
| QUANTIZATION_FACTOR = 10 |
|
|
| def convert_and_resize_image(image): |
| gray_image = image.convert("L") |
| w, h = gray_image.size |
| w_crop = w - (w % 8) |
| h_crop = h - (h % 8) |
| if w_crop == 0 or h_crop == 0: |
| return None |
| return gray_image.crop((0, 0, w_crop, h_crop)) |
|
|
| def message_to_binary(message): |
| message += "_END_" |
| return ''.join(format(ord(c), '08b') for c in message) |
|
|
| def binary_to_message(binary_message): |
| delimiter = ''.join(format(ord(c), '08b') for c in "_END_") |
| if delimiter not in binary_message: |
| return None |
| try: |
| end_index = binary_message.index(delimiter) |
| clean_binary = binary_message[:end_index] |
| if len(clean_binary) % 8 != 0: |
| return None |
| return ''.join(chr(int(clean_binary[i:i+8], 2)) for i in range(0, len(clean_binary), 8)) |
| except: |
| return None |
|
|
| def apply_dct(image_array): |
| h, w = image_array.shape |
| dct_blocks = np.zeros_like(image_array, dtype=float) |
| for i in range(0, h, 8): |
| for j in range(0, w, 8): |
| block = image_array[i:i+8, j:j+8].astype(float) |
| dct_blocks[i:i+8, j:j+8] = dct(dct(block.T, norm='ortho').T, norm='ortho') |
| return dct_blocks |
|
|
| def apply_idct(dct_blocks): |
| h, w = dct_blocks.shape |
| image_blocks = np.zeros_like(dct_blocks, dtype=float) |
| for i in range(0, h, 8): |
| for j in range(0, w, 8): |
| block = dct_blocks[i:i+8, j:j+8] |
| image_blocks[i:i+8, j:j+8] = idct(idct(block.T, norm='ortho').T, norm='ortho') |
| return np.clip(image_blocks, 0, 255).astype(np.uint8) |
|
|
| def embed_message(image, secret_message): |
| gray_cropped = convert_and_resize_image(image) |
| if gray_cropped is None: |
| return None |
| img_array = np.array(gray_cropped) |
| h, w = img_array.shape |
|
|
| binary_message = message_to_binary(secret_message) |
| msg_len = len(binary_message) |
|
|
| dct_coeffs = apply_dct(img_array) |
| bit_index = 0 |
| for i in range(0, h, 8): |
| for j in range(0, w, 8): |
| if bit_index >= msg_len: |
| break |
| u, v = 4, 1 |
| coeff = dct_coeffs[i + u, j + v] |
| bit = int(binary_message[bit_index]) |
| quantized_coeff = int(round(coeff / QUANTIZATION_FACTOR)) |
| if quantized_coeff % 2 != bit: |
| quantized_coeff -= 1 |
| dct_coeffs[i + u, j + v] = quantized_coeff * QUANTIZATION_FACTOR |
| bit_index += 1 |
| if bit_index >= msg_len: |
| break |
| stego_array = apply_idct(dct_coeffs) |
| return Image.fromarray(stego_array) |
|
|
| def extract_message(image): |
| gray_cropped = convert_and_resize_image(image) |
| if gray_cropped is None: |
| return None |
| img_array = np.array(gray_cropped) |
| h, w = img_array.shape |
| dct_coeffs = apply_dct(img_array) |
| binary_message = "" |
| for i in range(0, h, 8): |
| for j in range(0, w, 8): |
| u, v = 4, 1 |
| coeff = dct_coeffs[i + u, j + v] |
| quantized_coeff = int(round(coeff / QUANTIZATION_FACTOR)) |
| binary_message += str(quantized_coeff % 2) |
| return binary_to_message(binary_message) |
|
|
