期刊名称：International Journal of Advanced Robotic Systems
印刷版ISSN：1729-8806
电子版ISSN：1729-8814
出版年度：2012
卷号：9
期号：3
页码：80
DOI：10.5772/51470
语种：English
出版社：SAGE Publications
摘要：For criminal searches, the necessity of matching photographs with sketches is increasing. Previously, matching was performed manually by a human observer, a time-consuming process whose accuracy can be affected by the level of human expertise. Therefore, we propose a new face recognition algorithm for photographs and sketches. This research is novel in the following three ways. First, to overcome the decrease in matching accuracy due to pose and illumination variation, we use eye alignment and retinex filtering to normalize pose, size and illumination. Second, we compare the performance of various face recognition methods, such as principal component analysis (PCA), local binary pattern (LBP), local non-negative matrix factorization (LNMF), support vector machine-discriminant analysis (SVM-DA) and modified census transform (MCT), for the matching of photographs and viewed sketches. Third, these five face recognition methods are combined on the basis of score-level fusion to enhance matching accuracy, thereby overcoming the performance limitations of single face recognition methods. Experimental results using a CUHK dataset showed that the accuracy of the proposed method is better than that of uni-modal face recognition methods.
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