MINUTIA CYLINDER CODE-BASED FINGERPRINT MATCHING OPTIMIZATION USING GPU

The advancement and use of digital data are growing very rapidly along with the <br /> <br /> <br /> <br /> advancement of technology nowadays. In this digital era, lots of physical data have <br /> <br /> <br /> <br /> been transformed into th...

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Bibliographic Details
Main Author: VISAT SUTARNO (NIM : 13513037), MUHAMAD
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/23179
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:The advancement and use of digital data are growing very rapidly along with the <br /> <br /> <br /> <br /> advancement of technology nowadays. In this digital era, lots of physical data have <br /> <br /> <br /> <br /> been transformed into the digital ones. One example of the use of digital data is the <br /> <br /> <br /> <br /> digital biometric fingerprint data on the Electronic Identity Card (KTP-el). In 2010, <br /> <br /> <br /> <br /> the population of Indonesia is about 200 million people. We can imagine how long <br /> <br /> <br /> <br /> it would take to process their fingerprint's data if it is done linearly, which is what <br /> <br /> <br /> <br /> is currently happening. Thus, there is a need for a parallel fingerprint matching. <br /> <br /> <br /> <br /> Based on this rationale, this final project aims to improve the fingerprint matching <br /> <br /> <br /> <br /> performance, in the current state of the art linear solution, by using the Minutia <br /> <br /> <br /> <br /> Cylinder-Code (MCC) algorithm in parallel on GPU. The performance <br /> <br /> <br /> <br /> improvements are made in the area of the selection of data structures, the calculation <br /> <br /> <br /> <br /> of valid areas in parallel, the creation of cylinders and cylinders-sets minutiae in <br /> <br /> <br /> <br /> parallel, and global calculations in parallel. <br /> <br /> <br /> <br /> Based on the experiment and testing, the proposed solution has a significantly better <br /> <br /> <br /> <br /> run time compared to the state of the art linear solution while maintaining the <br /> <br /> <br /> <br /> accuracy of the fingerprint matching. The proposed solution can run 14.17 up to <br /> <br /> <br /> <br /> 37.82 times faster and the accuracy has only a small difference to the previous <br /> <br /> <br /> <br /> solution with a standard deviation of 0.33%.