Robust Face Recognition Under Illumination Changes and Pose Variations
Publish place: Journal of Computing and Security، Vol: 5، Issue: 2
Publish Year: 1397
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JCSE-5-2_004
تاریخ نمایه سازی: 21 فروردین 1400
Abstract:
There are many applications for face recognition. Due to illumination changes, and pose variations of facial images, face recognition is often a challenging and a complicated process. In this paper, we propose an effective and robust face recognition method. Firstly, we select those areas from the face (such as eyes, nose, and mouth), which are more informative in face recognition. Then SIFT (Scale Invariant Feature Transform) descriptor is utilized for feature extraction from the selected areas. SIFT descriptor detects keypoints in the image and describes each keypoint with a feature vector with length 128. To speed up the proposed method, PCA (Principal Component Analysis) is applied on the SIFT feature vector to reduce the vector’s length. Finally, Kepenekci matching method is used to assess similarity between the images. The proposed method is evaluated on the ORL, Extended Yale B, and FEI databases. Results show considerable performance of the proposed face recognition method in comparison with several state-of-the-arts.
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Authors
Hamid Hassanpour
Prof ., Faculty of Computer Engineering & IT, Shahrood University of Technology, Shahrood, Iran.
Omid Kohansal
Faculty of Computer Engineering & IT, Shahrood University of Technology, Prof. Shahrood, Iran.
Sekineh Asadi Amiri
Assistant professor, Facaulty of Technology and Engineering, University of Mazandaran, Babolsar, Iran.
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