Excellent MATLAB Code for Circular Object Detection

This post shares an advanced MATLAB implementation for detecting circular objects in digital images. The algorithm employs sophisticated techniques including Hough transform variation for circle detection, morphological operations for noise reduction, and edge detection for precise boundary identification. Key functionalities include automated circular target localization with sub-pixel accuracy, real-time diameter computation using Euclidean distance metrics, and area calculation through pixel counting with calibration factors. The code structure features modular design with separate functions for image preprocessing, candidate detection, validation filtering, and measurement output. Implementation highlights include adaptive thresholding for illumination invariance and circular Hough accumulator optimization for computational efficiency. This solution demonstrates robust performance across various imaging conditions and scales seamlessly from microscopic to aerial imagery. For technical implementation, the core algorithm utilizes MATLAB's Image Processing Toolbox functions like imfindcircles() with sensitivity optimization, regionprops() for geometrical measurements, and custom validation logic to eliminate false positives. The code includes comprehensive error handling and parameter tuning guidelines for different application scenarios. We welcome feedback, usage experiences, and suggestions for enhancement. Please feel free to share your implementation results or contact us for technical discussion. This resource aims to support researchers and engineers in computer vision projects requiring precise circular object analysis.