Yu-Chi Su, Ching-Te Chiu, Chih-Han Cheng, Kuan-Hsien Liu, Tsung-Chan Lee, Jia-Lin Chen, Jie-Yu Luo, Wei-Chang Chung, Yao-Ren Chang, Kuan-Ying Ho
{"title":"CPGAN: Collective Punishment Generative Adversarial Network for Dry Fingerprint Image Enhancement","authors":"Yu-Chi Su, Ching-Te Chiu, Chih-Han Cheng, Kuan-Hsien Liu, Tsung-Chan Lee, Jia-Lin Chen, Jie-Yu Luo, Wei-Chang Chung, Yao-Ren Chang, Kuan-Ying Ho","doi":"10.1109/AICAS57966.2023.10168628","DOIUrl":null,"url":null,"abstract":"Fingerprint has been widely used in our daily life, such as mobile. However, some circumstances may lead to low unlocking rate, like fingerprint at low temperature(dry fingerprint) or washed fingerprint. Our method mainly focuses on the former by making it close to normal temperature fingerprint. The main idea of our method, which called \"CPGAN\", is to improve GAN to boost the quality of the enhanced fingerprint. Our objective is to make the generator generates the high quality of enhanced fingerprint. The method is divided into two parts: \"strengthening the discriminator\" and \"strengthening the generator\". For strengthening the generator, we adopt the mechanism of \"Collective Punishment\" to our work. For strengthening the discriminator, we utilize two generators and feature extractor to boost the discriminator. In our experiments, the results surpass the state-of-the-arts on FVC2002 about 75%.","PeriodicalId":296649,"journal":{"name":"2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)","volume":"242 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICAS57966.2023.10168628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Fingerprint has been widely used in our daily life, such as mobile. However, some circumstances may lead to low unlocking rate, like fingerprint at low temperature(dry fingerprint) or washed fingerprint. Our method mainly focuses on the former by making it close to normal temperature fingerprint. The main idea of our method, which called "CPGAN", is to improve GAN to boost the quality of the enhanced fingerprint. Our objective is to make the generator generates the high quality of enhanced fingerprint. The method is divided into two parts: "strengthening the discriminator" and "strengthening the generator". For strengthening the generator, we adopt the mechanism of "Collective Punishment" to our work. For strengthening the discriminator, we utilize two generators and feature extractor to boost the discriminator. In our experiments, the results surpass the state-of-the-arts on FVC2002 about 75%.