Region-Division Vector Quantization Histogram Method for Human Face Recognition
| Autor: | Koji Kotani, Feifei Lee, Qiu Chen, Tadahiro Ohmi |
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| Rok vydání: | 2006 |
| Předmět: |
FERET database
Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Histogram matching Vector quantization Pattern recognition Facial recognition system Theoretical Computer Science Image (mathematics) Computational Theory and Mathematics Artificial Intelligence Face (geometry) Histogram Feature (machine learning) Computer vision Artificial intelligence business Software |
| Zdroj: | Intelligent Automation & Soft Computing. 12:257-268 |
| ISSN: | 2326-005X 1079-8587 |
| Popis: | We have developed a very simple yet highly reliable face recognition method called VQ histogram method codevector referred (or matched) count histogram, which is obtained by Vector Quantization (VQ) processing of facial image, is utilized as a very effective personal feature value. Furthermore, for adding the geometric information of the face to improve the recognition accuracy, aregion-division (RD) VQ histogram method is proposed in this paper. We divide the facial area into 5 regions relating to the facial parts (forehead, eye, nose, mouth, jaw). Recognition results with different parts are fast obtained separately and then combined by weighted averaging. Topl recognition rate of 97.4% is obtained by using FB task (1195 images) in the standard FERET database. By using the private database, which was taken in practical but yet reasonably regulated environrnent, Topl recognition rate of 100% is realized. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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