Face-sketch recognition using canonical correlation analysis

Hand-drawn face sketches are frequently used in criminal investigations. In this paper, we present a novel framework for face recognition from sketches. Our framework based is on Principle Component Analysis (PCA) and Canonical Correlation Analysis (CCA). First, we apply PCA to a dataset for dimension reduction and then apply CCA for reaching maximum correlation within a dataset. This approach is tested on two different datasets including 311 photo-sketch pairs. The performance reached 99.36% recognition rate on these experiments.