{"title":"照片图像中的水下目标识别","authors":"A. Pavin","doi":"10.23919/OCEANS.2015.7401926","DOIUrl":null,"url":null,"abstract":"The identification problem of artificial or natural objects in underwater images is considered in this paper. Any object (including a previously received image) with unequivocally determined contours can be used as a pattern. Recognition of the required object is made by an exhaustive search of key points or small pieces of borders with a subsequent increase of accumulator cells. Processing of real sea-bottom images has confirmed the algorithm's efficiency (including dead reckoning, marker recognition and line recognition tasks).","PeriodicalId":403976,"journal":{"name":"OCEANS 2015 - MTS/IEEE Washington","volume":"282 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Underwater object recognition in photo images\",\"authors\":\"A. Pavin\",\"doi\":\"10.23919/OCEANS.2015.7401926\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The identification problem of artificial or natural objects in underwater images is considered in this paper. Any object (including a previously received image) with unequivocally determined contours can be used as a pattern. Recognition of the required object is made by an exhaustive search of key points or small pieces of borders with a subsequent increase of accumulator cells. Processing of real sea-bottom images has confirmed the algorithm's efficiency (including dead reckoning, marker recognition and line recognition tasks).\",\"PeriodicalId\":403976,\"journal\":{\"name\":\"OCEANS 2015 - MTS/IEEE Washington\",\"volume\":\"282 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"OCEANS 2015 - MTS/IEEE Washington\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/OCEANS.2015.7401926\",\"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 2015 - MTS/IEEE Washington","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/OCEANS.2015.7401926","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The identification problem of artificial or natural objects in underwater images is considered in this paper. Any object (including a previously received image) with unequivocally determined contours can be used as a pattern. Recognition of the required object is made by an exhaustive search of key points or small pieces of borders with a subsequent increase of accumulator cells. Processing of real sea-bottom images has confirmed the algorithm's efficiency (including dead reckoning, marker recognition and line recognition tasks).
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