Facial Sketches are most widely used in law enforcement agencies for identification and apprehension of suspects, which may involve in several criminal activities. We plan to implement an efficient system to recognize a forensic sketch images to a gallery of mug shot images which will help law enforcement agencies. SIFT algorithm explained for feature extraction. This SIFT feature will possess strong robustness to the accessory, expression, pose, illumination variations. SIFT algorithm have highest percentage of accuracy. Faces are highly deformable objects which may easily change their appearance over time. The feature based sketch matching algorithm (SIFT) we present offers both a simpler and faster design and utilizes localized sketch information in the matching process. SIFT used for extracting local features. Scale invariant feature transform (SIFT) proposed by Lowe has been widely and successfully applied to object detection and recognition. SIFT algorithm's ability has been leveraged through use of MATLAB code. This helps users to use SIFT algorithm very effectively to match sketches with current database images
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