S. Sudiro, I. P. Wardhani, B. A. Wardijono, Brian Handias
{"title":"Fingerprint matching application using hardware based artificial neural network with Matlab","authors":"S. Sudiro, I. P. Wardhani, B. A. Wardijono, Brian Handias","doi":"10.1109/ICEEIE.2017.8328764","DOIUrl":null,"url":null,"abstract":"Biometric-based system is one of the systems for identification/recognition and verification. There are many types of biometric technology, one of them is fingerprint recognition system. Fingerprint, like other biometric feature is unique, means that it will always different with its kind. One of the problems in fingerprint recognition systems is how to extract the characteristics/feature of a person's fingerprint. This article present fingerprint matching application as part of recognition, using simple minutiae point extraction algorithm implemented it into hardware-based Artificial Neural Network device. The Cogniblox is an ANN device from CogniMem that comes with 4 CM1K chip, able to store up to 4096 neurons in the device. MATLAB environment is used for developing the fingerprint recognition application. The designed system is then undergo a performance evaluation by recognizing a total of 80 dataset of fingerprint, consist of 10 different fingerprint with 8 impression each, which stored into the neurons beforehand. The performance evaluation resulted in a False Acceptance Rate (FAR), False Rejection Rate (FRR) and Equal Error Rate (EER) are presented.","PeriodicalId":304532,"journal":{"name":"2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEIE.2017.8328764","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Biometric-based system is one of the systems for identification/recognition and verification. There are many types of biometric technology, one of them is fingerprint recognition system. Fingerprint, like other biometric feature is unique, means that it will always different with its kind. One of the problems in fingerprint recognition systems is how to extract the characteristics/feature of a person's fingerprint. This article present fingerprint matching application as part of recognition, using simple minutiae point extraction algorithm implemented it into hardware-based Artificial Neural Network device. The Cogniblox is an ANN device from CogniMem that comes with 4 CM1K chip, able to store up to 4096 neurons in the device. MATLAB environment is used for developing the fingerprint recognition application. The designed system is then undergo a performance evaluation by recognizing a total of 80 dataset of fingerprint, consist of 10 different fingerprint with 8 impression each, which stored into the neurons beforehand. The performance evaluation resulted in a False Acceptance Rate (FAR), False Rejection Rate (FRR) and Equal Error Rate (EER) are presented.