An Efficient Human Face Recognition Approach: Combination of Eigenface and k-Means Clustering methods - Softcover

Bag, Soumen

Softcover

ISBN 10: 3843378304 ISBN 13: 9783843378307

Verlag: LAP LAMBERT Academic Publishing, 2010

Inhaltsangabe

Facial expressions convey non verbal cues, which play an important role in interpersonal relations. Automatic recognition of human face based on facial expression can be important component of natural human-machine interface. It may also be used in behavioral science. Although human can recognize the face practically without any effort, but reliable face recognition by machine is a challenge. This book presents a new approach for recognizing the face of a person considering the expression of the same human face at different instant of time. This methodology is developed combining Eigenface method for feature extraction and k-Means clustering for identification of the human face. In experimental purpose, AT&T face database is used which contains a set of 40 people with 10 images with different facial expressions at the different illumination. Experimental results demonstrate the efficacy of the approach. This book is written such a manner that it will help researchers to work on the area of image processing and pattern recognition. It also helps graduate students to know the background and basic theories of different face recognition methods.

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Über die Autorin bzw. den Autor

Soumen Bag received his B.E. and M.Tech degree in ComputerScience & Engineering from NIT Durgapur, India in 2003 and 2008respectively. At Present he has been a Research Scholar in IITKharagpur, India. His research interests are in Image Processing,OCR for Indian scripts, and Pattern Recognition. He is the authorof 5 conference papers.

Details zur Ausgabe

• Verlag: LAP LAMBERT Academic Publishing
• Erscheinungsdatum: 2010
• Sprache: Englisch
• ISBN 10: 3843378304
• ISBN 13: 9783843378307
• Einband: Taschenbuch
• Anzahl der Seiten: 72
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: SIA OmniScriptum Publishing; customerservice@vdm-vsg.de; ; Brivibas gatve 197; Riga; 1039; Lettland