TY  - JOUR
AU  - Razzaq, Ali Nadhim 
AU  - Hussain, Zahir M. 
AU  - Mohammed, Hind Rustum 
PY  - 2016
TI  - Structural Geodesic-Tchebychev Transform: An Image Similarity Measure for Face Recognition
JF  - Journal of Computer Science
VL  - 12
IS  - 9
DO  - 10.3844/jcssp.2016.464.470
UR  - https://thescipub.com/abstract/jcssp.2016.464.470
AB  - This work presents a new holistic measure for face recognition. Face recognition involves three steps: Face Detection, Feature Extraction and Matching. In the face detection process to identify the face area in face images, Viola-Jones algorithm has been used. Feature extraction is based on performing double-transformation, where discrete Tchebychev transform is performed on the geodesic distance transform of the grayscale image. Structural Similarity (SSIM) is applied to the resulting image double-transform to find matching factor with other image faces in the FEI (Brazilian) database. Performance is measured using a confidence criterion based on the similarity distance between the recognized person (best match) and the next possible ambiguity (second-best match). Simulation results showed that the proposed approach handles the face recognition efficiently as compared with SSIM.