Partial fingerprint matching using projection based weak descriptor

Often in forensic scenarios, need arises to map a partial or poor quality finger print to the identity of an individual. The general image matching methods found in computer vision perform poorly as they are sensitive to local distortions like broken ridge patterns and incomplete information. To address this issue, we propose to use a weak descriptor to capture local structures at a higher abstract level. The goal here is to mine a large set of initial correspondence through weak description and then rely on robust estimator scheme to prune false matches. By coupling weak local descriptor with robust estimator, we minimize the affect of broken ridge patterns and also obtain a dense set of matches for a given pair. We evaluate the performance of the proposed method against SIFT as per the Fingerprint Verification Competition guidelines. We also report superior performance of the current methods rotation, scale, noise and overlap handling capabilities.