  To recognize face sketch through face photo database is a challenging task
for todays researchers. Because face photo images in training set and face
sketch images in testing set have different modality. Difference between two
face photos of difference person is smaller than the difference between same
person in a face photo and face sketched. In this paper, for reduction of the
modality between face photo and face sketch we first bring face photo and face
sketch images in a new dimension using 2D Discrete Haar wavelet transform with
scale 3 followed by a negative approach. After that, extract features from
transformed images using Principal Component Analysis (PCA). Thereafter, we use
SVM classifier and K-NN classifier for better classification. Our proposed
method is experimentally verified by its robustness against faces that are
captured in a good lighting condition and in a frontal pose. The experiment has
been conducted with 100 male and female face images as training set and 100
male and female face sketch images as testing set collected from CUHK training
and testing cropped photos and CUHK training and testing cropped sketches.
