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shoe mark, histogram, image processing

In every criminal investigation it is necessary to determine and prove that a particular person or persons may or may not have been present at the scene of a crime. For this reasons, the collection, preservation and analysis of physical evidence has become more frequent in the law enforcement community[5]. Since criminals must enter and exit crime scene areas, it should therefore, be reasonably assumed that they may leave traces of their own footwear. Criminals have become smarter and wiser by beginning to frequently wear protection over their hands to avoid leaving fingerprints, and masks over their faces to avoid eyewitness identification. However, they are rarely aware of, or make little attempt to conceal footwear. During an every day routine it is normal to see individual wearing gloves, but it’s not so over their shoes. In shoe print biometrics one of the important tasks is the preparation of reference data from the available sources. But to use these images for feature extraction and recovery from data bases requires certain steps like conversion to gray scale, image enhancement before storage of reference image and image restoration. In this paper we have taken example shoe image from a commercial web site and converted it to gray scale to reduce the size of storage then enhanced the image using histogram technique. Image is ready for analysis by various techniques. Keywords: Image processing, shoe mark, histogram, constrained least squares method, segmentation