Rapid Circle Detection Method Based on Hough Transform

This document presents a rapid circle detection method developed using Hough Transform principles on the MATLAB platform. The implementation utilizes gradient information and accumulator arrays to efficiently identify circular patterns in images. Key algorithm steps include edge detection using operators like Canny, gradient calculation, and Hough space voting for circle parameter estimation. This methodology proves particularly effective for iris image analysis, enabling fast and accurate localization of both inner (pupil) and outer (limbus) iris boundaries. Iris detection serves as a critical technology for biometric authentication systems. Our approach incorporates radius constraints and sampling optimization to enhance processing speed while maintaining detection accuracy. By implementing this method, developers can streamline iris detection workflows, achieving superior edge localization precision that significantly improves recognition reliability and system performance. The MATLAB implementation includes functions for parameter tuning, visualization of detected circles, and validation metrics for accuracy assessment.