Liukui Chen, Xiaoxing Wang, H. Jiang, Li Tang, Zuojin Li, Yao Du
{"title":"基于树莓派的手掌静脉平台及模式增强模型设计","authors":"Liukui Chen, Xiaoxing Wang, H. Jiang, Li Tang, Zuojin Li, Yao Du","doi":"10.1109/ICESIT53460.2021.9696490","DOIUrl":null,"url":null,"abstract":"In recent years, with the rapid development of biometrics technology, vein recognition is slowly integrating into our lives. At present, there are many related applications of hand veins and finger veins. The palm veins are deep under the skin and interfere with palm prints, which increases the difficulty of obtaining them, resulting in relatively few applications. Based on the research of palm vein image acquisition, this paper designs a set of auxiliary acquisition equipment to complete the acquisition of vein images under a comfortable somatosensory. The device takes the Raspberry Pi as the core of the model, supplemented by accessories such as luminous light source, optical sensor, control chip and small display, which can complete the collection of vein images. And through the algorithm of restricted contrast histogram equalization, Gaussian denoising, gabor filtering and other algorithms optimized for palm veins in the Raspberry Pi, the palm vein lines are enhanced to improve the image quality. The model integrates multiple modules into one mold, greatly reduces the volume of the model, improves the speed of the overall collection process, and has good application value.","PeriodicalId":164745,"journal":{"name":"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design of Palm Vein Platform and Pattern Enhancement Model Based on Raspberry Pi\",\"authors\":\"Liukui Chen, Xiaoxing Wang, H. Jiang, Li Tang, Zuojin Li, Yao Du\",\"doi\":\"10.1109/ICESIT53460.2021.9696490\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, with the rapid development of biometrics technology, vein recognition is slowly integrating into our lives. At present, there are many related applications of hand veins and finger veins. The palm veins are deep under the skin and interfere with palm prints, which increases the difficulty of obtaining them, resulting in relatively few applications. Based on the research of palm vein image acquisition, this paper designs a set of auxiliary acquisition equipment to complete the acquisition of vein images under a comfortable somatosensory. The device takes the Raspberry Pi as the core of the model, supplemented by accessories such as luminous light source, optical sensor, control chip and small display, which can complete the collection of vein images. And through the algorithm of restricted contrast histogram equalization, Gaussian denoising, gabor filtering and other algorithms optimized for palm veins in the Raspberry Pi, the palm vein lines are enhanced to improve the image quality. The model integrates multiple modules into one mold, greatly reduces the volume of the model, improves the speed of the overall collection process, and has good application value.\",\"PeriodicalId\":164745,\"journal\":{\"name\":\"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICESIT53460.2021.9696490\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICESIT53460.2021.9696490","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of Palm Vein Platform and Pattern Enhancement Model Based on Raspberry Pi
In recent years, with the rapid development of biometrics technology, vein recognition is slowly integrating into our lives. At present, there are many related applications of hand veins and finger veins. The palm veins are deep under the skin and interfere with palm prints, which increases the difficulty of obtaining them, resulting in relatively few applications. Based on the research of palm vein image acquisition, this paper designs a set of auxiliary acquisition equipment to complete the acquisition of vein images under a comfortable somatosensory. The device takes the Raspberry Pi as the core of the model, supplemented by accessories such as luminous light source, optical sensor, control chip and small display, which can complete the collection of vein images. And through the algorithm of restricted contrast histogram equalization, Gaussian denoising, gabor filtering and other algorithms optimized for palm veins in the Raspberry Pi, the palm vein lines are enhanced to improve the image quality. The model integrates multiple modules into one mold, greatly reduces the volume of the model, improves the speed of the overall collection process, and has good application value.