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Face sketch synthesis has wide applications ranging from digitalentertainments to law enforcements. Objective image quality assessment scoresand face recognition accuracy are two mainly used tools to evaluate thesynthesis performance. In this paper, we proposed a synthesized face sketchrecognition framework based on full-reference image quality assessment metrics.Synthesized sketches generated from four state-of-the-art methods are utilizedto test the performance of the proposed recognition framework. For the imagequality assessment metrics, we employed the classical structured similarityindex metric and other three prevalent metrics: visual information fidelity,feature similarity index metric and gradient magnitude similarity deviation.Extensive experiments compared with baseline methods illustrate theeffectiveness of the proposed synthesized face sketch recognition framework.Data and implementation code in this paper are available online atwww.ihitworld.com/WNN/IQA_Sketch.zip.

Training-Free Synthesized Face Sketch Recognition Using Image Quality Assessment Metrics