Otsu's Maximum Inter-class Variance Method for Image Segmentation using MATLAB
This algorithm implements Otsu's maximum inter-class variance method, utilizing MATLAB for effective image segmentation with code implementation details
Image Thresholding Using Fuzzy C-Means Clustering Algorithm
This code implements image thresholding using fuzzy c-means clustering, demonstrating superior performance compared to traditional Otsu's method for various image types.
MATLAB Implementation of Binarization Algorithms with Code Examples
Comprehensive binarization algorithm implementations including Otsu, Niblack, Kapur, and Kittler-Met methods with MATLAB code demonstrations and performance analysis
Otsu's Multilevel Thresholding Method for Image Segmentation
Otsu's multilevel thresholding method is an advanced image processing technique that automatically determines optimal threshold values for effective segmentation, particularly useful for images with complex backgrounds or uneven illumination through intra-class variance minimization.
Classic Otsu Thresholding Algorithm for Image Segmentation
Classic Otsu Algorithm for Automated Image Thresholding