Document Type
Journal Article
Publisher
Science Publications
School
School of Engineering
RAS ID
22665
Funders
Ministry of Higher Education & Scientific Research (Iraq)
Edith Cowan University
Abstract
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.
DOI
10.3844/jcssp.2016.464.470
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Razzaq, A., Hussain, Z., Mohammed, H. (2016). Structural geodesic-Tchebychev transform: An Image similarity measure for face recognition. Journal of Computer Sciences. 12(9), 464-470.
https://doi.org/10.3844/jcssp.2016.464.470