Analysis of Face Recognition using Manhattan Distance Algorithm with Image Segmentation?

Segmentation is one of the important concepts in Face Recognition. Based on the segmentation, the image is to be identified by different algorithms such as Euclidean distance, Manhattan distance, Chebyshev distance and other methods. In this paper, the segmentation concept with Manhattan algorithm to produce the visible image and focus on the exact segmented image with Manhattan distance algorithm. This algorithm compares the given face with a database of faces of ORL2. It recognizes the particular face and then the segmented part of the image to be produced, depends on the users choice. The recognition rate of the image segmentation shows the result accurately with 97% compared with Euclidean distance. It also produces the FAR and FRR of the given image.