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It is the intention of this work to develop a system which specialized in processing scanned images. This paper focuses on developing an extended partitioning approach for partial fingerprint identification. The procedure has utilized image orientation, enhancement, extended-partitioning, binarization and feature extraction. The major focus of this work is to reduce error rates during match. The proposed approach performs partitioning on images to create extended sub-parts before matching. This procedure clinically extracts the information of sub-parts and establishes a lower bound on the performance. The extended partition-based representation combines both the global and the local information present in a fingerprint. Test results have presented that the proposed method has a discriminatory power compared to other representations. Finally, it has shown that the use of all the techniques presented in this work significantly improves error rates of a partial fingerprint identification system on a large database.

e-PARFIT: An Extended Partition-Based Approach in Automated Fingerprint Identification System for Partial Images