{"title":"重新审视图像分割","authors":"A. Mérigot","doi":"10.1109/ICIAP.2003.1234069","DOIUrl":null,"url":null,"abstract":"The paper presents a modified version of the classical split and merge algorithm (Horowitz, S. and Pavlidis, T., 1976). Instead of performing a regular decomposition of the image, it relies on a split at an optimal position that makes a good interregion separation. The implementation of the algorithm uses an initial image preprocessing to speed-up computation. Experimental results show that the number of regions generated by the split phase is largely reduced and that the distortion of the segmented image is smaller, while the execution time is slightly increased.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Revisiting image splitting\",\"authors\":\"A. Mérigot\",\"doi\":\"10.1109/ICIAP.2003.1234069\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a modified version of the classical split and merge algorithm (Horowitz, S. and Pavlidis, T., 1976). Instead of performing a regular decomposition of the image, it relies on a split at an optimal position that makes a good interregion separation. The implementation of the algorithm uses an initial image preprocessing to speed-up computation. Experimental results show that the number of regions generated by the split phase is largely reduced and that the distortion of the segmented image is smaller, while the execution time is slightly increased.\",\"PeriodicalId\":218076,\"journal\":{\"name\":\"12th International Conference on Image Analysis and Processing, 2003.Proceedings.\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"12th International Conference on Image Analysis and Processing, 2003.Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIAP.2003.1234069\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAP.2003.1234069","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
摘要
本文提出了经典分割和合并算法的改进版本(Horowitz, S. and Pavlidis, T., 1976)。它不是对图像进行常规分解,而是依赖于在最佳位置进行分割,从而实现良好的区域间分离。该算法的实现采用初始图像预处理来加快计算速度。实验结果表明,分割相位产生的区域数量大大减少,分割图像的失真较小,而执行时间略有增加。
The paper presents a modified version of the classical split and merge algorithm (Horowitz, S. and Pavlidis, T., 1976). Instead of performing a regular decomposition of the image, it relies on a split at an optimal position that makes a good interregion separation. The implementation of the algorithm uses an initial image preprocessing to speed-up computation. Experimental results show that the number of regions generated by the split phase is largely reduced and that the distortion of the segmented image is smaller, while the execution time is slightly increased.