Adaptive Threshold-Based Foreground-Background Separation Algorithm Under Irregular Illumination

This MATLAB implementation provides an adaptive threshold algorithm designed specifically for foreground-background separation under challenging irregular illumination conditions. The implementation includes test images for reference and validation purposes. The algorithm offers the following features and advantages: - Utilizes adaptive thresholding techniques to effectively separate foreground objects from background elements across varying illumination conditions, making it robust to lighting inconsistencies. - Demonstrates strong performance in irregular lighting scenarios by accurately detecting and segmenting target objects from complex backgrounds using dynamic threshold calculation methods. - Implemented using MATLAB's image processing toolbox, featuring key functions like adaptthresh() and imbinarize() for creating locally adaptive thresholds and converting images to binary format. The code structure allows for easy customization of neighborhood size and sensitivity parameters. - Includes comprehensive test images that enable users to validate the algorithm's accuracy and performance metrics, including precision in object detection and boundary segmentation quality. The implementation provides commented MATLAB scripts with adjustable parameters for threshold sensitivity and kernel size, allowing researchers and developers to adapt the algorithm to specific application requirements. The modular code structure facilitates integration into larger computer vision pipelines. We hope this algorithm proves valuable for your image processing and computer vision applications!