Image Region of Interest Extraction with Binary Masking

This MATLAB code demonstrates how to extract regions of interest (ROI) from images and apply binary masking to visualize the extracted objects across all three color channels. The implementation begins by importing essential image processing libraries using MATLAB's Image Processing Toolbox functions. The code loads the target image using imread() and displays it with imshow() for initial visualization. ROI selection can be performed through interactive methods like roipoly() for polygon selection or createMask() with ROI drawing tools for precise boundary definition. The core algorithm involves generating a binary mask where pixels within the selected region are set to 1 (white) while background pixels are set to 0 (black). This mask is then applied to each color channel (Red, Green, Blue) using element-wise multiplication (.* operator) to isolate the ROI while maintaining color integrity. The extracted object is preserved with its original colors, while the background is masked out. Key functions utilized include: - im2bw() or imbinarize() for mask creation - bwlabel() for connected component analysis - regionprops() for extracting morphological properties - Logical indexing for efficient channel separation This implementation provides valuable insights into fundamental image processing workflows and can be adapted for various applications including computer vision systems, medical imaging analysis, and object detection pipelines. The code demonstrates practical techniques for image segmentation and region-based processing. We hope this code proves useful for your image processing projects. Please feel free to ask if you have any technical questions or require further clarification on the implementation details.