{"title":"基于SNAM表示的二值图像几何计算算法","authors":"Caixu Xu, Guo Hui, He Jie","doi":"10.1109/CIS52066.2020.00012","DOIUrl":null,"url":null,"abstract":"Aiming at problems such as difficulties in determini--ng sub-mode position relations and complexity in image calculations caused by asymmetric segmentation in SNAM image representation, the present study first recovers submodule spatial position relations of SNAM representation with grid arrays and improves the grid arrays satisfying geometric calculation of images. Then, it proposes a geometric calculation algorithm based on SNAM. According to experimental results compared to geometric calculations represented by linear quad-tree and arrays or the like, the proposed algorithm has obvious higher efficiency. It is an eight-neighborhood image geometric calculation algorithm with excellent performance and adaptability to SNAM representation.","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\":\"Binary Image Geometric Calculation Algorithm Based on SNAM Representation\",\"authors\":\"Caixu Xu, Guo Hui, He Jie\",\"doi\":\"10.1109/CIS52066.2020.00012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at problems such as difficulties in determini--ng sub-mode position relations and complexity in image calculations caused by asymmetric segmentation in SNAM image representation, the present study first recovers submodule spatial position relations of SNAM representation with grid arrays and improves the grid arrays satisfying geometric calculation of images. Then, it proposes a geometric calculation algorithm based on SNAM. According to experimental results compared to geometric calculations represented by linear quad-tree and arrays or the like, the proposed algorithm has obvious higher efficiency. It is an eight-neighborhood image geometric calculation algorithm with excellent performance and adaptability to SNAM representation.\",\"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/CIS52066.2020.00012\",\"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/CIS52066.2020.00012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Binary Image Geometric Calculation Algorithm Based on SNAM Representation
Aiming at problems such as difficulties in determini--ng sub-mode position relations and complexity in image calculations caused by asymmetric segmentation in SNAM image representation, the present study first recovers submodule spatial position relations of SNAM representation with grid arrays and improves the grid arrays satisfying geometric calculation of images. Then, it proposes a geometric calculation algorithm based on SNAM. According to experimental results compared to geometric calculations represented by linear quad-tree and arrays or the like, the proposed algorithm has obvious higher efficiency. It is an eight-neighborhood image geometric calculation algorithm with excellent performance and adaptability to SNAM representation.
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