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Face Recognition using Vector Quantization. A novel approach to Face Recognition
В наличии
| Местонахождение: Алматы | Состояние экземпляра: новый |
Бумажная
версия
версия
Автор: Prachi Natu,Shachi Natu and Tanuja Sarode
ISBN: 9783659154317
Год издания: 2012
Формат книги: 60×90/16 (145×215 мм)
Количество страниц: 96
Издательство: LAP LAMBERT Academic Publishing
Цена: 31069 тг
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Отрасли знаний:Код товара: 481751
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Аннотация: This book presents a novel approach for Face Recognition using ‘Vector Quantization’. Face Recognition is one of the popular biometric techniques used in today’s era. A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. Vector quantization is simple image compression technique. It is efficient for image coding because it reduces computational complexity. VQ compression is highly asymmetric in processing time: choosing an optimal codebook takes huge amounts of calculations, but decompression is lightning-fast—only one table lookup per vector. This makes VQ an excellent choice for face recognition. In this book four different VQ algorithms namely LBG, KPE, KMCG and KFCG are used to observe the efficiency of face recognition system. Efficiency is calculated in terms of recognition rate and computational complexity. It has been observed that KPE, KMCG and KFCG outperform LBG which is known as benchmark in vector quantization. Proposed techniques are compared with traditional DCT and Walsh transform also. It proves better than transform techniques.
Ключевые слова: Face recognition, vector quantization, Feature vector, codebook
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