Document Type

Journal Article

Publisher

Science Publications

School

School of Engineering

RAS ID

22665

Comments

Originally published as: 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. Original article available here

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

http://dx.doi.org/10.3844/jcssp.2016.464.470

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

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Engineering Commons

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