FACE RECOGNITION BY RING ROTATION INVARIANT TRANSFORM AND MANAGING IMAGE ROTATION AND SHIFTING PROBLEMS

Abstract

Generally, for face recognition, image shift and rotation problems must be addressed. The "ring rotation invariant transform" technique is used to transfer geometrical features of face image to other more salient ones; by which one can identify whether a sample or unknown image is the identical image. It also can solve image rotation problem. To deal with the image-shifting problem, this study uses one pixel inside a sample image to compare with the corresponding pixels in the unknown image to locate the closest matching point. In this study, three different kinds of extracted ring signals are generated, which are (1) ring-radius-31, (2) ring-radius-22, and (3) ring-radius-13. These signals are used to generate the rotation invariant magnitudes and several magnitudes are combined as one entity and, subsequently, saved inside one specific corresponding pixel in the BMP file. By this approach, one pixel will possess more geometrical-features of the face images; one entity in sample image is compared with entities inside the corresponding radius-6-cake area of the unknown image to locate the closest matching point.