{"title":"基于视觉系统特征的地形图线性元素分离与种子传播","authors":"Fei Xie, Yanning Zhang, Xinming Guo, Wei Zhang, Zhaoyong Zhou, Pengfei Xu","doi":"10.1109/CIS52066.2020.00011","DOIUrl":null,"url":null,"abstract":"In topographic maps, It is difficult to separate the linear elements, including contour lines, roads, latitude and longitude lines from complicated background due to the pixels with aliasing and false colors, and there exists some background in the result images extracted by the existing methods, especially when the color and energy of linear elements and background are similar in some particular maps, or the maps have low contrast contour lines. To solve these problems, this paper introduces the idea of seed spreading, and puts forward a novel method for separating linear elements. In this method, all the seeds carry the color information of the pixels and the energy information in the negative grayscale images, and they can search other pixels as their brothers to be combined into seed groups according to the color and energy similarity. The seeds have good perception of the environment around them, and the shapes of the seed groups are variable. Furthermore, the seeds are determined as linear elements by analyzing the color and energy differences between the seed groups and the areas around them. The experimental results show that our method can distinguish linear elements from the background more accurately than the previous methods.","PeriodicalId":106959,"journal":{"name":"2020 16th International Conference on Computational Intelligence and Security (CIS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Linear Elements Separation via Vision System Feature and Seed Spreading from Topographic Maps\",\"authors\":\"Fei Xie, Yanning Zhang, Xinming Guo, Wei Zhang, Zhaoyong Zhou, Pengfei Xu\",\"doi\":\"10.1109/CIS52066.2020.00011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In topographic maps, It is difficult to separate the linear elements, including contour lines, roads, latitude and longitude lines from complicated background due to the pixels with aliasing and false colors, and there exists some background in the result images extracted by the existing methods, especially when the color and energy of linear elements and background are similar in some particular maps, or the maps have low contrast contour lines. To solve these problems, this paper introduces the idea of seed spreading, and puts forward a novel method for separating linear elements. In this method, all the seeds carry the color information of the pixels and the energy information in the negative grayscale images, and they can search other pixels as their brothers to be combined into seed groups according to the color and energy similarity. The seeds have good perception of the environment around them, and the shapes of the seed groups are variable. Furthermore, the seeds are determined as linear elements by analyzing the color and energy differences between the seed groups and the areas around them. The experimental results show that our method can distinguish linear elements from the background more accurately than the previous methods.\",\"PeriodicalId\":106959,\"journal\":{\"name\":\"2020 16th International Conference on Computational Intelligence and Security (CIS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 16th International Conference on Computational Intelligence and Security (CIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS52066.2020.00011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 16th International Conference on Computational Intelligence and Security (CIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS52066.2020.00011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Linear Elements Separation via Vision System Feature and Seed Spreading from Topographic Maps
In topographic maps, It is difficult to separate the linear elements, including contour lines, roads, latitude and longitude lines from complicated background due to the pixels with aliasing and false colors, and there exists some background in the result images extracted by the existing methods, especially when the color and energy of linear elements and background are similar in some particular maps, or the maps have low contrast contour lines. To solve these problems, this paper introduces the idea of seed spreading, and puts forward a novel method for separating linear elements. In this method, all the seeds carry the color information of the pixels and the energy information in the negative grayscale images, and they can search other pixels as their brothers to be combined into seed groups according to the color and energy similarity. The seeds have good perception of the environment around them, and the shapes of the seed groups are variable. Furthermore, the seeds are determined as linear elements by analyzing the color and energy differences between the seed groups and the areas around them. The experimental results show that our method can distinguish linear elements from the background more accurately than the previous methods.