Researchers are always on the move to innovate something new from their side. Such a work by researchers in the field of biometrics has led to identify the finger knuckle print as a biometric trait with distinct features. There are certain biometric parts such as fingerprint, iris, palm print and now knuckle print. Knuckle contains rich texture that is distinct for each fingers it selves. Knuckle has potential information that can differentiate persons uniquely. System is intended to acquire the knuckle image and process it for data acquisition and generate code map. Code map is a template that localized in database and compare with input code maps. The proposed system is able to extract information from knuckle image with high precision using different kind of filters and image enhancement techniques such as Gabor, Spatial filters and Sobel that facilitate SURF (Speeded Up Robust Feature). Proposed system possess low error rate with zero false recognition recall. If a system has false acceptance rate then the precision does not follow ideal system. System should have zero false acceptance and high false rejection rate along with true acceptance. Precision is based on high quality feature extraction that could be made by some image enhancement techniques that proposed system follows.

Knuckle Print, Sobel Edge Detection, SURF, Gabor Filter, Biometric and Binary Localization

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