Benner
أ.هند رستم شعبان ( أستاذ )
كلية علوم الحاسوب والرياضيات - الحاسوب
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Structural Geodesic-Tchebychev Transform: An Image Similarity Measure for Face Recognition
تحميل
بحث النوع:
علوم التخصص العام:
Ali Nadhim Razzaq اسم الناشر:
Zahir M. Hussain and Hind Rustum Mohammed اسماء المساعدين:
American Journal of Applied Sciences, . الجهة الناشرة:
Scopus H-index =18 (see http://www.scimagojr.com/journalrank.php ). 10.3844/ajassp.2016  
2016 سنة النشر:

الخلاصة

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. Keywords: Discrete Tchebychev Moments, Generalized Geodesy via Geodesic Time, Structural Similarity (SSIM), Viola-Jones, Face Recognition, Image Processing