Face Sketch Generationof Example Image by Encoding Local Binary Pattern

Facesketchsynthesis of example image plays an important role in both digital entertainment and law enforcement. In this paper, face sketch synthesis has two main processes. In the first process, neighbors are selected and in the second process, reconstruction weight representation is done.Running time and computation complexity depends on neighbor patches selection process.Face sketchgeneration with state-of-the-art methods perform neighbor selection process in a data-driven manner by K nearest neighbor searching. Hence, the running time for synthesisincreases.Also, for neighbor selection need to check the whole training dataset. As a result, the computational complexity increases with the scale of the training database and is limited scalability. In this paper, we proposed a simple but effective with encoding local binary pattern and random sampling in place of pixels. Then by extracting shape from resulting textures and determining state of surfaces, we represent facial sketch. Our experiments onpair of CUHK database imagesdemonstrate the proposed method in comparison to state-of-the-art methods has superiorityof view generated sketch quality and running time. Also, the proposed methodin front of face hallucinationproblemswhich cause heterogeneous transformation on facial sketch is resistant.