Memetically Optimized MCWLD for Matching Sketches With Digital Face Images
Memetically Optimized MCWLD for Matching Sketches With Digital Face Images
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DOI：
10.1109/tifs.2012.2204252
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发表时间：
2012-10-01
影响因子：
6.8
通讯作者：
Vatsa, Mayank
中科院分区：
文献类型：
--
作者：
Bhatt, Himanshu S.;Bharadwaj, Samarth;Vatsa, Mayank
破案和逮捕罪犯的重要线索之一是将草图与数字人脸图像进行匹配。本文提出了一种自动算法，用于从草图和数字人脸图像的局部区域中提取区分信息。使用多尺度圆形韦伯局部描述符对局部面部区域中存在的结构信息以及微小细节进行编码。此外，提出了一种进化模因优化算法，为每个局部面部区域分配最佳权重，以提高识别性能。由于法医草图或数字人脸图像的质量可能较差，因此使用预处理技术来提高图像质量并提高识别性能。对不同草图数据库的综合实验评估表明，与现有人脸识别算法和两种商用人脸识别系统相比，该算法具有更好的识别性能。
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.