{"title":"基于均值移位和分水岭变换的矿石图像自动分割","authors":"A. Amankwah, C. Aldrich","doi":"10.1109/RADIOELEK.2011.5936391","DOIUrl":null,"url":null,"abstract":"In this paper, we present a novel method for segmenting ore images specifically for estimating the size distribution of ore material on conveyer belt. The segmentation system uses the mean shift and watershed algorithm. The mean shift algorithm is used to identify pixel clusters of particular modes of the probability density function of the image data. The pixel clusters are then used to generate markers for the watershed transform and shadow areas in ore image. Experimental results show that the proposed algorithm is not only faster than the standard methods but also more robust.","PeriodicalId":267447,"journal":{"name":"Proceedings of 21st International Conference Radioelektronika 2011","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Automatic ore image segmentation using mean shift and watershed transform\",\"authors\":\"A. Amankwah, C. Aldrich\",\"doi\":\"10.1109/RADIOELEK.2011.5936391\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a novel method for segmenting ore images specifically for estimating the size distribution of ore material on conveyer belt. The segmentation system uses the mean shift and watershed algorithm. The mean shift algorithm is used to identify pixel clusters of particular modes of the probability density function of the image data. The pixel clusters are then used to generate markers for the watershed transform and shadow areas in ore image. Experimental results show that the proposed algorithm is not only faster than the standard methods but also more robust.\",\"PeriodicalId\":267447,\"journal\":{\"name\":\"Proceedings of 21st International Conference Radioelektronika 2011\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 21st International Conference Radioelektronika 2011\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADIOELEK.2011.5936391\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 21st International Conference Radioelektronika 2011","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADIOELEK.2011.5936391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic ore image segmentation using mean shift and watershed transform
In this paper, we present a novel method for segmenting ore images specifically for estimating the size distribution of ore material on conveyer belt. The segmentation system uses the mean shift and watershed algorithm. The mean shift algorithm is used to identify pixel clusters of particular modes of the probability density function of the image data. The pixel clusters are then used to generate markers for the watershed transform and shadow areas in ore image. Experimental results show that the proposed algorithm is not only faster than the standard methods but also more robust.
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