Improving face recognition by elman neural network using curvelet transform and HSI color space

Ahmed S. S. Abdullah, Majida Ali Abed, Israa Al Barazanchi

Abstract


In this paper, a suggested algorithm was proposed to increase the efficiency of the Elman neural algorithm in face recognition. The proposed algorithm was studied on the images of 20 students from the Department of Computer Science, Tikrit University. First step creates dataset of faces, second step convert color space to HSI and using saturation layer, image decomposition using curvelet transform, feature extraction using Principle component analysis, and final step face recognition using Elman neural network. after applying proposed algorithm, the rate of face recognition 94%.

Keywords


face recognition, image processing, color space, neural network, curve let transform.

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DOI: http://dx.doi.org/10.21533/pen.v7i2.485

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Copyright (c) 2019 Ahmed S. S. Abdullah

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License