Current research on matching sketches with digital face images has primarily focused on hand drawn sketches. However, law enforcement agencies are now using software tools to generate composite sketches. In this paper, we propose a face recognition algorithm to match composite sketches with digital face images. The contribution of this research is three fold: (1) proposing feature extraction and matching algorithm using visual saliency and combination of texture features, (2) incorporating attributes for re-ordering the ranked list, and (3) utilizing multiple experts such as multiple composite sketch generation tools or artists for improving the matching performance. The results computed on the extended PRIP database show that the proposed algorithm improves the state-of-art in matching composite sketch and digital face images and yields the rank 50 identification accuracy of 81.3%.
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