Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2011-07-14
Computer Science
Computer Vision and Pattern Recognition
24 pages
Scientific paper
Face recognition has been studied extensively for more than 20 years now. Since the beginning of 90s the subject has became a major issue. This technology is used in many important real-world applications, such as video surveillance, smart cards, database security, internet and intranet access. This report reviews recent two algorithms for face recognition which take advantage of a relatively new multiscale geometric analysis tool - Curvelet transform, for facial processing and feature extraction. This transform proves to be efficient especially due to its good ability to detect curves and lines, which characterize the human's face. An algorithm which is based on the two algorithms mentioned above is proposed, and its performance is evaluated on three data bases of faces: AT&T (ORL), Essex Grimace and Georgia-Tech. k-nearest neighbour (k-NN) and Support vector machine (SVM) classifiers are used, along with Principal Component Analysis (PCA) for dimensionality reduction. This algorithm shows good results, and it even outperforms other algorithms in some cases.
No associations
LandOfFree
Face Recognition using Curvelet Transform does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Face Recognition using Curvelet Transform, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Face Recognition using Curvelet Transform will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-225070