Edge Detection Using Phase Congruency

This program implements edge detection using phase congruency. Compared with conventional intensity-based edge detection algorithms, this approach is illumination-independent and demonstrates strong noise resistance. During the edge detection process, phase congruency can more accurately capture edge information in images, thereby providing more precise detection results. The algorithm maintains high accuracy even under complex lighting conditions where intensity-based methods typically struggle. Key implementation aspects include calculating local energy maps through quadrature filter pairs and detecting edges where Fourier components are maximally in phase. The phase congruency approach effectively minimizes noise impact by focusing on phase information rather than amplitude, significantly improving edge detection quality. Additional implementation details involve multi-scale orientation analysis using Log-Gabor filters and non-maximum suppression for edge thinning. This program therefore delivers more reliable, stable, and accurate edge detection functionality suitable for robust computer vision applications.