Research Paper on Edge Detection Using Block based Segmentation

Edge detection is an important image processing technique with wide range of applications. Several edge detection algorithms have been developed in the past few decades, however no single algorithm is suitable for all types of applications. Face recognition is one such important application in which edge detection plays a key role. Edge maps help in representing faces as a single unit. Here we survey the existing edge detection techniques and their suitability for extracting edges from facial images under noisy conditions. Then we introduce the proposed algorithm which is optimized for extracting edge maps from facial images under normal and noisy conditions. The proposed method is optimized for extracting edges from images corrupted by various types of noises. Performance of several existing edge detectors is severely degraded under noisy conditions. However, using the proposed method we are able to consistently detect good quality edge maps under various levels of noises.