M. Toda, K. Enomoto, Y. Kuwahara, M. Wada, K. Hatanaka
{"title":"用于渔业资源调查的海底图像扇贝面积提取方法","authors":"M. Toda, K. Enomoto, Y. Kuwahara, M. Wada, K. Hatanaka","doi":"10.1109/OCEANS.2008.5151901","DOIUrl":null,"url":null,"abstract":"In this research, we propose a method to extract scallop areas in seabed images in order to construct a system that can measure automatically the number, size, and state of fishery resources, especially scallops, by analyzing seabed images. Our algorithm is based on information on the hue and characteristic pattern scallop shells. The effectiveness of the proposed method is illustrated through an experiment.","PeriodicalId":113677,"journal":{"name":"OCEANS 2008","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Extraction method of scallop area in seabed images for fishery resources investigation\",\"authors\":\"M. Toda, K. Enomoto, Y. Kuwahara, M. Wada, K. Hatanaka\",\"doi\":\"10.1109/OCEANS.2008.5151901\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this research, we propose a method to extract scallop areas in seabed images in order to construct a system that can measure automatically the number, size, and state of fishery resources, especially scallops, by analyzing seabed images. Our algorithm is based on information on the hue and characteristic pattern scallop shells. The effectiveness of the proposed method is illustrated through an experiment.\",\"PeriodicalId\":113677,\"journal\":{\"name\":\"OCEANS 2008\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"OCEANS 2008\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OCEANS.2008.5151901\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"OCEANS 2008","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCEANS.2008.5151901","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extraction method of scallop area in seabed images for fishery resources investigation
In this research, we propose a method to extract scallop areas in seabed images in order to construct a system that can measure automatically the number, size, and state of fishery resources, especially scallops, by analyzing seabed images. Our algorithm is based on information on the hue and characteristic pattern scallop shells. The effectiveness of the proposed method is illustrated through an experiment.
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