Face recognition with Gabor phase

Face recognition is an attractive biometric measure due to its capacity to recognize individuals without their cooperation. This thesis proposes a method to dynamically recognize a facial image with the help of its valid features. To validate a set of feature points, the skin portion of the facial i...

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Main Author: Venkata, Anjaneya Subha Chaitanya Konduri
Other Authors: Watkins, John Michael
Format: Others
Language:en_US
Published: Wichita State University 2010
Online Access:http://hdl.handle.net/10057/2508
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spelling ndltd-WICHITA-oai-soar.wichita.edu-10057-25082013-04-19T21:00:01ZFace recognition with Gabor phaseVenkata, Anjaneya Subha Chaitanya KonduriFace recognition is an attractive biometric measure due to its capacity to recognize individuals without their cooperation. This thesis proposes a method to dynamically recognize a facial image with the help of its valid features. To validate a set of feature points, the skin portion of the facial image is identified by processing each pixel value. Gabor phase samples are examined, depending on whether they are positive or negative at each filter output, and feature vectors are formed with positive or negative ones along with the spatial coordinates at the validated feature points. The collection of feature vectors is referred to as the feature vector set. The face recognition system has two phases: training and recognition. During the training phase, all images from the database are automatically loaded into the system, and their feature vector set is determined. When the test image arrives at the system, the feature vector set of the test image is compared with that of database images. Feature vectors are location-specific, and thereby similarities between the feature vectors of the test image and database images are calculated, provided that they are from the same spatial coordinates. Once spatial coordinates are matched by using exclusive-OR (X-OR) operation, the similarity is calculated from the values of the feature vector. Simulations using the proposed scheme have shown that precise recognition can be achieved.Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer ScienceWichita State UniversityWatkins, John Michael2010-09-01T15:12:05Z2010-09-01T15:12:05Z2009-07Thesisx, 37 P.530781 bytesapplication/pdft09050http://hdl.handle.net/10057/2508en_US
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description Face recognition is an attractive biometric measure due to its capacity to recognize individuals without their cooperation. This thesis proposes a method to dynamically recognize a facial image with the help of its valid features. To validate a set of feature points, the skin portion of the facial image is identified by processing each pixel value. Gabor phase samples are examined, depending on whether they are positive or negative at each filter output, and feature vectors are formed with positive or negative ones along with the spatial coordinates at the validated feature points. The collection of feature vectors is referred to as the feature vector set. The face recognition system has two phases: training and recognition. During the training phase, all images from the database are automatically loaded into the system, and their feature vector set is determined. When the test image arrives at the system, the feature vector set of the test image is compared with that of database images. Feature vectors are location-specific, and thereby similarities between the feature vectors of the test image and database images are calculated, provided that they are from the same spatial coordinates. Once spatial coordinates are matched by using exclusive-OR (X-OR) operation, the similarity is calculated from the values of the feature vector. Simulations using the proposed scheme have shown that precise recognition can be achieved. === Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
author2 Watkins, John Michael
author_facet Watkins, John Michael
Venkata, Anjaneya Subha Chaitanya Konduri
author Venkata, Anjaneya Subha Chaitanya Konduri
spellingShingle Venkata, Anjaneya Subha Chaitanya Konduri
Face recognition with Gabor phase
author_sort Venkata, Anjaneya Subha Chaitanya Konduri
title Face recognition with Gabor phase
title_short Face recognition with Gabor phase
title_full Face recognition with Gabor phase
title_fullStr Face recognition with Gabor phase
title_full_unstemmed Face recognition with Gabor phase
title_sort face recognition with gabor phase
publisher Wichita State University
publishDate 2010
url http://hdl.handle.net/10057/2508
work_keys_str_mv AT venkataanjaneyasubhachaitanyakonduri facerecognitionwithgaborphase
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