Finding the Minimum Bounding Rectangle for Target Regions in Binary Images

In a given binary image, our objective is to locate the minimum rectangular bounding box that encompasses the target region. To achieve this, we first calculate the top, bottom, left, and right boundary coordinates. Common implementation approaches involve scanning the image pixels to detect the target region's contours and using functions like cv2.boundingRect() in OpenCV or regionprops() in MATLAB to automatically extract these boundaries. Once the coordinates are obtained, we can draw the bounding rectangle on the image for visualization. This method offers the advantage of clearly displaying the target’s position and dimensions within the image, enabling better analysis and interpretation of the region. Consequently, it supports informed decision-making in subsequent image processing steps. Therefore, when working with binary images, it is essential to compute the minimum bounding box for target regions and visualize it on the image to facilitate further operations.