{"title":"基于遗传算法的数字曲线多边形逼近","authors":"P. B. Alvarado-Velazco, V. Ayala-Ramírez","doi":"10.1109/ICIT.2012.6209947","DOIUrl":null,"url":null,"abstract":"We present a method to approximate a digital curve with a straight line sequence. The curve approximation curve has been posed as an optimization problem, and a genetic algorithm is used to solve such a problem. The proposed approach outputs a set of ending points for the line segments used to encode the resulting polygonal approximation. We have tested our method with a curve dataset composed of 11 open and closed curves. The results show that the proposed method performs qualitatively well on the test dataset. We show also quantitative measures of the similarity between the original input curve and the results of the genetic algorithm-based optimization process.","PeriodicalId":365141,"journal":{"name":"2012 IEEE International Conference on Industrial Technology","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Polygonal approximation of digital curves using genetic algorithms\",\"authors\":\"P. B. Alvarado-Velazco, V. Ayala-Ramírez\",\"doi\":\"10.1109/ICIT.2012.6209947\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a method to approximate a digital curve with a straight line sequence. The curve approximation curve has been posed as an optimization problem, and a genetic algorithm is used to solve such a problem. The proposed approach outputs a set of ending points for the line segments used to encode the resulting polygonal approximation. We have tested our method with a curve dataset composed of 11 open and closed curves. The results show that the proposed method performs qualitatively well on the test dataset. We show also quantitative measures of the similarity between the original input curve and the results of the genetic algorithm-based optimization process.\",\"PeriodicalId\":365141,\"journal\":{\"name\":\"2012 IEEE International Conference on Industrial Technology\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Industrial Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIT.2012.6209947\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Industrial Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2012.6209947","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Polygonal approximation of digital curves using genetic algorithms
We present a method to approximate a digital curve with a straight line sequence. The curve approximation curve has been posed as an optimization problem, and a genetic algorithm is used to solve such a problem. The proposed approach outputs a set of ending points for the line segments used to encode the resulting polygonal approximation. We have tested our method with a curve dataset composed of 11 open and closed curves. The results show that the proposed method performs qualitatively well on the test dataset. We show also quantitative measures of the similarity between the original input curve and the results of the genetic algorithm-based optimization process.