{"title":"一种改进的迷宫算法在captcha轮廓提取中的应用","authors":"Jialin Liu, Kaifa Liang, Shuangping Chen","doi":"10.1109/KAM.2010.5646230","DOIUrl":null,"url":null,"abstract":"An improved maze algorithm has been first advanced, combining with the rotation invariant theory, to extract the contour of CAPTCHAs which are slant and have random positions. First, take the CAPTCHAs as a maze, in which white pixels represents a potential route; Second, search towards “left-down” in the predefined direction and record the pixels which have been checked; Finally, get the clockwise rotate projection of CAPTCHAs within the paths' closed region in order to obtain the CAPTCHAs' contour features which are immune to rotation, random position, slant and other factors. Experiments have shown that the algorithm has better performance in dealing with CAPTCHAs which are slant and have random positions, its sufficient extraction of contour features reduces errors and improves recognition rate.","PeriodicalId":160788,"journal":{"name":"2010 Third International Symposium on Knowledge Acquisition and Modeling","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An improved maze algorithm in contour extraction of CAPTCHAs\",\"authors\":\"Jialin Liu, Kaifa Liang, Shuangping Chen\",\"doi\":\"10.1109/KAM.2010.5646230\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An improved maze algorithm has been first advanced, combining with the rotation invariant theory, to extract the contour of CAPTCHAs which are slant and have random positions. First, take the CAPTCHAs as a maze, in which white pixels represents a potential route; Second, search towards “left-down” in the predefined direction and record the pixels which have been checked; Finally, get the clockwise rotate projection of CAPTCHAs within the paths' closed region in order to obtain the CAPTCHAs' contour features which are immune to rotation, random position, slant and other factors. Experiments have shown that the algorithm has better performance in dealing with CAPTCHAs which are slant and have random positions, its sufficient extraction of contour features reduces errors and improves recognition rate.\",\"PeriodicalId\":160788,\"journal\":{\"name\":\"2010 Third International Symposium on Knowledge Acquisition and Modeling\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Third International Symposium on Knowledge Acquisition and Modeling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KAM.2010.5646230\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Symposium on Knowledge Acquisition and Modeling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KAM.2010.5646230","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An improved maze algorithm in contour extraction of CAPTCHAs
An improved maze algorithm has been first advanced, combining with the rotation invariant theory, to extract the contour of CAPTCHAs which are slant and have random positions. First, take the CAPTCHAs as a maze, in which white pixels represents a potential route; Second, search towards “left-down” in the predefined direction and record the pixels which have been checked; Finally, get the clockwise rotate projection of CAPTCHAs within the paths' closed region in order to obtain the CAPTCHAs' contour features which are immune to rotation, random position, slant and other factors. Experiments have shown that the algorithm has better performance in dealing with CAPTCHAs which are slant and have random positions, its sufficient extraction of contour features reduces errors and improves recognition rate.