Journal of Computer Science

Structural Geodesic-Tchebychev Transform: An Image Similarity Measure for Face Recognition

Ali Nadhim Razzaq, Zahir M. Hussain and Hind Rustum Mohammed

DOI : 10.3844/jcssp.2016.464.470

Journal of Computer Science

Volume 12, Issue 9

Pages 464-470


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.


© 2016 Ali Nadhim Razzaq, Zahir M. Hussain and Hind Rustum Mohammed. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.