{"title":"基于加速鲁棒特征的菠萝实时匹配系统","authors":"Bin Li, Maohua Wang, Li Li","doi":"10.1109/CIS.2010.59","DOIUrl":null,"url":null,"abstract":"Real-time and accurate image matching is a key to stereo vision of agricultural harvesting robots. This research is part of a pineapple harvesting robot project. In this paper, pineapples were selected as research objects and low cost binocular vision platform was constructed, fruit area of left image was got by real-time image acquisition and rapid segmentation, rapid matching of fruit area in left image with the integral right image was done by employing SURF (Speeded-Up Robust Features) algorithm. The algorithm was programmed and tested in VC++ software and the results showed that, the segmentation cost 0.017s and the real-time matching performed well. Compared with other agricultural harvesting robots’ research, area matching and real-time matching were well-realized.","PeriodicalId":420515,"journal":{"name":"2010 International Conference on Computational Intelligence and Security","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Real-Time Pineapple Matching System Based on Speeded-Up Robust Features\",\"authors\":\"Bin Li, Maohua Wang, Li Li\",\"doi\":\"10.1109/CIS.2010.59\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Real-time and accurate image matching is a key to stereo vision of agricultural harvesting robots. This research is part of a pineapple harvesting robot project. In this paper, pineapples were selected as research objects and low cost binocular vision platform was constructed, fruit area of left image was got by real-time image acquisition and rapid segmentation, rapid matching of fruit area in left image with the integral right image was done by employing SURF (Speeded-Up Robust Features) algorithm. The algorithm was programmed and tested in VC++ software and the results showed that, the segmentation cost 0.017s and the real-time matching performed well. Compared with other agricultural harvesting robots’ research, area matching and real-time matching were well-realized.\",\"PeriodicalId\":420515,\"journal\":{\"name\":\"2010 International Conference on Computational Intelligence and Security\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Computational Intelligence and Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.2010.59\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Computational Intelligence and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2010.59","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Real-Time Pineapple Matching System Based on Speeded-Up Robust Features
Real-time and accurate image matching is a key to stereo vision of agricultural harvesting robots. This research is part of a pineapple harvesting robot project. In this paper, pineapples were selected as research objects and low cost binocular vision platform was constructed, fruit area of left image was got by real-time image acquisition and rapid segmentation, rapid matching of fruit area in left image with the integral right image was done by employing SURF (Speeded-Up Robust Features) algorithm. The algorithm was programmed and tested in VC++ software and the results showed that, the segmentation cost 0.017s and the real-time matching performed well. Compared with other agricultural harvesting robots’ research, area matching and real-time matching were well-realized.
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