Phase Congruency Detection for Edge Extraction

In the MATLAB environment, phase congruency detection serves as an effective method for extracting target edges from images. This signal processing technique operates by analyzing phase information similarity between signals. The implementation typically involves converting images to the frequency domain using Fast Fourier Transform (FFT), followed by applying band-pass filters (such as Log-Gabor filters) to reduce noise and irrelevant components. Key MATLAB functions include fft2() for frequency transformation and imag() for phase extraction. The phase congruency algorithm then calculates local energy maxima where phase components align, effectively identifying edges regardless of illumination variations. This method proves particularly valuable in applications like object detection, image segmentation, and medical image processing due to its illumination-invariant properties. Post-processing steps may involve edge thinning and thresholding using functions like bwmorph() to refine the detected edges for further analysis.