信号和图像处理分配附matlab代码.zip

# Retinal Blood Vessel Segmentation ## Problem The code aims to perform retinal blood vessel segmentation using various image processing techniques. Additionally, it includes a validation function to assess the accuracy of the segmentation results compared to ground truth data. ## Mathematical model - Image Processing Techniques: The code implements several image processing steps to segment blood vessels by using Filtering and Thresholding Techniques like Gaussian filtering, erosion (using a diamond-shaped structuring element), principal curvature calculation, contrast enhancement (histogram equalization), and thresholding are used to identify blood vessels. - Validation Technique: The validation function compares the segmented image with a ground truth image to compute accuracy metrics in the training phase. ## Selected methods 1. Structuring Element and Erosion: A diamond-shaped structuring element (strel('diamond', 20)) is applied for erosion to refine the mask. 2. Gaussian Filter: Gaussian filtering (imgaussfilt) with a sigma value of 1.45 is used to smoothen the green channel of the input image. 3. Principal Curvature Calculation: A function prinCur calculates the principal curvature of the filtered image. 4. Histogram Equalization and Thresholding: Adaptive histogram equalization (adapthisteq) is performed on the calculated curvature. Thresholding (isodata) is used to segment the vessels. ## Test cases Demonstrations 1- Training Phase: - Reads training images. - Processes each image using the described pipeline. - Generates segmented images and saves them in the processed folder. - Displays intermediate processing steps if the mode is 'train'.   - The validation function assesses segmentation accuracy by comparing the segmented image with ground truth data. It calculates metrics like True Positive Rate (TPR), False Positive Rate (FPR), and Accuracy (AC).  2- Testing Phase: - Reads test images. - Applies the same processing pipeline. - Saves the resulting segmented images in the results folder. - Displays intermediate steps if the mode is 'test' (commented out in the code). - There is no validation here as I don’t have ground truth values in the test folder database to compare with.