MINUTIA CYLINDER CODE-BASED FINGERPRINT MATCHING OPTIMIZATION USING GPU - VISAT SUTARNO (NIM : 13513037), MUHAMAD
The advancement and use of digital data are growing very rapidly along with the advancement of technology nowadays. In this digital era, lots of physical data have been transformed into the digital ones. One example of the use of digital data is the digital biometric fingerprint data on the Electronic Identity Card (KTP-el). In 2010, the population of Indonesia is about 200 million people. We can imagine how long it would take to process their fingerprint's data if it is done linearly, which is what is currently happening. Thus, there is a need for a parallel fingerprint matching. Based on this rationale, this final project aims to improve the fingerprint matching performance, in the current state of the art linear solution, by using the Minutia Cylinder-Code (MCC) algorithm in parallel on GPU. The performance improvements are made in the area of the selection of data structures, the calculation of valid areas in parallel, the creation of cylinders and cylinders-sets minutiae in parallel, and global calculations in parallel. Based on the experiment and testing, the proposed solution has a significantly better run time compared to the state of the art linear solution while maintaining the accuracy of the fingerprint matching. The proposed solution can run 14.17 up to 37.82 times faster and the accuracy has only a small difference to the previous solution with a standard deviation of 0.33%.