Overlapped Fingerprint Separation Based on DeepLearning

• Main Authors: CHEN,CHIH-KUN, 陳志焜
• Other Authors: HONG,GUO-MING
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/r239xa

碩士 === 開南大學 === 資訊學院碩士在職專班 === 106 === Biometrics and Artificial Intelligence are important infrastructures for the development of science and technology in various countries in the future. Fingerprint Identification is the most widely used and long-term application in biometric technology. Fingerprint Identification Technology has been quite mature so far, but fingerprint identification has mostly been used to explore Single Fingerprint. Recognition, the discussion of two or more Overlapped Fingerprints is relatively rare, but overlapping fingerprints is common in many criminal cases. Overlapping fingerprints have the phenomenon that the fingerprint lines interfere or cover each other. The complexity of the overlapping fingerprints is much higher than that of a single fingerprint. The difficulty in making judgments and understanding is also relatively high. At present, the recognition of overlapping fingerprints must be based on well-trained training. The personnel manually separated the fingerprint overlapping area from the non-overlapping area, which is a problem in personnel training and processing timeliness. Since the computer defeated the world chess king, artificial intelligence is the most concerned computer technology topic now, and the most important technology of artificial intelligence is Deep Learning.The main purpose of this paper is to apply the deep learning to automatically mark the overlapped and nonoverlapped regions of overlapped fingerprints.In this way, the overlapping area and the nonoverlapped area can be separated.In the case of identification of overlapping fingerprints that can be applied in criminal cases.I hope to contribute to and help with the collection of evidence in criminal cases and the speed with which cases can be solved.