MATLAB Implementation of Automatic Threshold Segmentation

This documentation presents an automatic threshold segmentation method implemented using MATLAB, providing two .m files for reference and study. Automatic threshold segmentation is a fundamental image processing technique that automatically determines optimal segmentation thresholds based on image histogram analysis, effectively partitioning images into distinct regions. The implementation employs histogram analysis algorithms such as Otsu's method or adaptive thresholding to calculate optimal separation points between foreground and background pixels. Key functions include grayscale histogram computation, threshold optimization algorithms, and binary image generation. Through parameter adjustments in the threshold calculation process, users can control segmentation precision and optimize results for different image characteristics. This approach enhances understanding and application of image processing techniques, offering valuable insights for research and practical implementations in computer vision projects.