Source Code for One-Dimensional Adaptive Threshold Segmentation Using Otsu's Method

This source code implements one-dimensional adaptive threshold segmentation using Otsu's method through MATLAB programming. The program utilizes MATLAB's image processing capabilities to apply Otsu's thresholding algorithm, which automatically determines the optimal segmentation threshold based on image grayscale characteristics. The implementation includes key functions for histogram calculation, between-class variance computation, and threshold optimization. The algorithm works by maximizing the inter-class variance between background and foreground pixels, ensuring automatic image segmentation without manual threshold specification. During development, we prioritized algorithm reliability and computational efficiency, incorporating vectorized operations for improved performance in practical applications. The code structure allows for easy parameter adjustments and optimization based on specific image processing requirements. Overall, this implementation serves as a valuable and practical tool for enhanced image data processing and analysis, particularly useful for automated image segmentation tasks in computer vision applications.