{"title":"3D reconstruction of apple fruits using consumer-grade RGB-depth sensor","authors":"Satoshi Yamamoto , Manoj Karkee , Yuichi Kobayashi , Natsuki Nakayama , Shogo Tsubota , Loan Nguyen Thi Thanh , Tomoko Konya","doi":"10.1016/j.eaef.2018.02.005","DOIUrl":null,"url":null,"abstract":"<div><p><span>Three-dimensional reconstruction has great potential to improve not only the post-harvest quality control but also the breeding efficiency in horticulture. The depth information of the consumer-grade RGB-depth sensor was unreliable compared to that obtained from industrial sensors. To cope with this disadvantage, the generated point cloud was corrected within a region of interest of the target fruit, which was extracted from the color image of the sensor. Evaluating more than a hundred apple fruits, the root-mean-square error of the volume and the largest diameter were less than 6 cm</span><sup>3</sup> and 1 mm, respectively. Reconstruction of various kinds of fruits and vegetables were demonstrated. The proposed method can be applied to accelerate the quantification of three-dimensional features of agricultural products.</p></div>","PeriodicalId":38965,"journal":{"name":"Engineering in Agriculture, Environment and Food","volume":"11 4","pages":"Pages 159-168"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.eaef.2018.02.005","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering in Agriculture, Environment and Food","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1881836617300459","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 14
Abstract
Three-dimensional reconstruction has great potential to improve not only the post-harvest quality control but also the breeding efficiency in horticulture. The depth information of the consumer-grade RGB-depth sensor was unreliable compared to that obtained from industrial sensors. To cope with this disadvantage, the generated point cloud was corrected within a region of interest of the target fruit, which was extracted from the color image of the sensor. Evaluating more than a hundred apple fruits, the root-mean-square error of the volume and the largest diameter were less than 6 cm3 and 1 mm, respectively. Reconstruction of various kinds of fruits and vegetables were demonstrated. The proposed method can be applied to accelerate the quantification of three-dimensional features of agricultural products.
期刊介绍：
Engineering in Agriculture, Environment and Food (EAEF) is devoted to the advancement and dissemination of scientific and technical knowledge concerning agricultural machinery, tillage, terramechanics, precision farming, agricultural instrumentation, sensors, bio-robotics, systems automation, processing of agricultural products and foods, quality evaluation and food safety, waste treatment and management, environmental control, energy utilization agricultural systems engineering, bio-informatics, computer simulation, computational mechanics, farm work systems and mechanized cropping. It is an international English E-journal published and distributed by the Asian Agricultural and Biological Engineering Association (AABEA). Authors should submit the manuscript file written by MS Word through a web site. The manuscript must be approved by the author''s organization prior to submission if required. Contact the societies which you belong to, if you have any question on manuscript submission or on the Journal EAEF.
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