Explore MATLAB source code curated for "OTSU算法" with clean implementations, documentation, and examples.
MATLAB implementation of the basic OTSU algorithm for determining optimal image threshold values. This algorithm automates the process of finding the best threshold for image binarization by maximizing inter-class variance.
Implementation of Otsu's thresholding algorithm for images without using built-in functions, featuring low-level code implementation
MATLAB implementation of Canny edge detection utilizing adaptive threshold selection based on Otsu's algorithm for optimal edge extraction
Implementation of Otsu's algorithm for adaptive threshold calculation and image binarization, includes histogram equalization program for enhanced image processing results
Image binarization algorithms including Otsu's method, Kittler minimum error thresholding, and Niblack binarization. These are classical algorithms for converting images to binary format. The implementations are custom-coded and thoroughly tested for correctness. The attachment contains detailed usage instructions with code examples and parameter explanations.
OTSU: A Simplified Implementation of Otsu's Algorithm for Determining Optimal Thresholds
MATLAB code implementation of Canny edge detection with detailed algorithm explanation and adaptive thresholding using Otsu's method.
Three Classic Image Segmentation Algorithms with Code-Related Explanations
MATLAB code implementation of Otsu's thresholding algorithm with statistical optimization for image segmentation