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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bhatt, H.S. Bharadwaj, S. Singh, R. Vatsa, M. |
| Copyright Year | 2005 |
| Abstract | One of the important cues in solving crimes and apprehending criminals is matching sketches with digital face images. This paper presents an automated algorithm to extract discriminating information from local regions of both sketches and digital face images. Structural information along with minute details present in local facial regions are encoded using multiscale circular Weber's local descriptor. Further, an evolutionary memetic optimization algorithm is proposed to assign optimal weight to every local facial region to boost the identification performance. Since forensic sketches or digital face images can be of poor quality, a preprocessing technique is used to enhance the quality of images and improve the identification performance. Comprehensive experimental evaluation on different sketch databases show that the proposed algorithm yields better identification performance compared to existing face recognition algorithms and two commercial face recognition systems. |
| Sponsorship | IEEE Signal Processing Society |
| Starting Page | 1522 |
| Ending Page | 1535 |
| Page Count | 14 |
| File Size | 2503518 |
| File Format | |
| ISSN | 15566013 |
| Volume Number | 7 |
| Issue Number | 5 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-10-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Face Forensics Face recognition Digital images Databases Algorithm design and analysis Memetics Weber's local descriptor forensic sketch memetic algorithm sketch recognition |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Networks and Communications Safety, Risk, Reliability and Quality |
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