{"title":"基于hough变换的虹膜定位实时应用的可行性","authors":"Klaus D. Tönnies, F. Behrens, Melanie Aurnhammer","doi":"10.1109/ICPR.2002.1048486","DOIUrl":null,"url":null,"abstract":"We present a fast method for locating iris features in frontal face images based on the Hough transform. it consists of an initial iris detection step and a tracking step which uses iris features from initialisation for speeding lip computation. The purpose of research was to evaluate the feasibility of the method for tracking at 200 frames per second or higher. Processing speed of the prototypical implementation on a 266 Mhz Pentium II PC is approximately 6 seconds for initial iris detection and about 0.05 seconds for each tracking step. Further speed-up using faster equipment seems feasible. The algorithm was applied to images of subjects taken under normal room lighting conditions. Tests showed robustness with respect to shadowing and partial occlusion of the iris. The localisation error was below two pixels. Accuracy for tracking was within one pixel. A reduction of the number of pixels, which are processed in the tracking step by 90% showed a modest degradation of the results.","PeriodicalId":159502,"journal":{"name":"Object recognition supported by user interaction for service robots","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"43","resultStr":"{\"title\":\"Feasibility of Hough-transform-based iris localisation for real-time-application\",\"authors\":\"Klaus D. Tönnies, F. Behrens, Melanie Aurnhammer\",\"doi\":\"10.1109/ICPR.2002.1048486\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a fast method for locating iris features in frontal face images based on the Hough transform. it consists of an initial iris detection step and a tracking step which uses iris features from initialisation for speeding lip computation. The purpose of research was to evaluate the feasibility of the method for tracking at 200 frames per second or higher. Processing speed of the prototypical implementation on a 266 Mhz Pentium II PC is approximately 6 seconds for initial iris detection and about 0.05 seconds for each tracking step. Further speed-up using faster equipment seems feasible. The algorithm was applied to images of subjects taken under normal room lighting conditions. Tests showed robustness with respect to shadowing and partial occlusion of the iris. The localisation error was below two pixels. Accuracy for tracking was within one pixel. A reduction of the number of pixels, which are processed in the tracking step by 90% showed a modest degradation of the results.\",\"PeriodicalId\":159502,\"journal\":{\"name\":\"Object recognition supported by user interaction for service robots\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"43\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Object recognition supported by user interaction for service robots\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2002.1048486\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Object recognition supported by user interaction for service robots","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2002.1048486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 43
摘要
提出了一种基于霍夫变换的人脸正面图像虹膜特征快速定位方法。它由初始虹膜检测步骤和跟踪步骤组成,跟踪步骤利用初始化虹膜特征来加速唇部计算。研究的目的是评估该方法在200帧/秒或更高速度下跟踪的可行性。在266 Mhz的Pentium II PC上,原型实现的初始虹膜检测处理速度约为6秒,每个跟踪步骤约为0.05秒。使用更快的设备进一步加速似乎是可行的。该算法应用于在正常室内照明条件下拍摄的受试者图像。测试显示了对虹膜阴影和部分遮挡的稳健性。定位错误低于两个像素。跟踪精度在一个像素以内。在跟踪步骤中处理的像素数量减少90%,显示出结果的适度退化。
Feasibility of Hough-transform-based iris localisation for real-time-application
We present a fast method for locating iris features in frontal face images based on the Hough transform. it consists of an initial iris detection step and a tracking step which uses iris features from initialisation for speeding lip computation. The purpose of research was to evaluate the feasibility of the method for tracking at 200 frames per second or higher. Processing speed of the prototypical implementation on a 266 Mhz Pentium II PC is approximately 6 seconds for initial iris detection and about 0.05 seconds for each tracking step. Further speed-up using faster equipment seems feasible. The algorithm was applied to images of subjects taken under normal room lighting conditions. Tests showed robustness with respect to shadowing and partial occlusion of the iris. The localisation error was below two pixels. Accuracy for tracking was within one pixel. A reduction of the number of pixels, which are processed in the tracking step by 90% showed a modest degradation of the results.