Detection of Circular Image Regions with Varying Radii

Detection of circular regions with varying radii in images can be achieved through image processing algorithms. This functionality proves highly valuable across multiple application domains. In computer vision, it facilitates object detection and recognition tasks using techniques like Hough Circle Transform implemented through functions such as cv2.HoughCircles() in OpenCV. In medical imaging, the algorithm assists in identifying lesions and tumors by analyzing circular patterns in diagnostic images with parameter optimization for different radius ranges. Industrial applications benefit from this capability for defect detection and quality control processes, where circular components can be examined using radial scanning methods and contour analysis. By detecting circular regions in images, we extract valuable information about image content, enabling further analytical processing through circular ROI extraction, feature measurement, and pattern classification algorithms.