  Face sketch synthesis has wide applications ranging from digital
entertainments to law enforcements. Objective image quality assessment scores
and face recognition accuracy are two mainly used tools to evaluate the
synthesis performance. In this paper, we proposed a synthesized face sketch
recognition framework based on full-reference image quality assessment metrics.
Synthesized sketches generated from four state-of-the-art methods are utilized
to test the performance of the proposed recognition framework. For the image
quality assessment metrics, we employed the classical structured similarity
index 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 the
effectiveness of the proposed synthesized face sketch recognition framework.
Data and implementation code in this paper are available online at
www.ihitworld.com/WNN/IQA_Sketch.zip.
