{"title":"使用随机森林算法根据从拍摄图像中提取的外部特征对芒果的质量进行分级","authors":"Nguyen Minh Trieu, Nguyen Truong Thinh","doi":"10.18178/joig.11.4.391-396","DOIUrl":null,"url":null,"abstract":"The grading of mango is still a manual process in agriculture. Nowadays, mangoes are classified based on human experience, which makes the grade not uniform for agricultural product export establishments. Therefore, the automated grading of mango is very important to solve these problems. In this study, a random forest algorithm is proposed for an automated mango grading system based on quality attributes such as density, surface defect, and weight. The internal features including dimensions and surface defects are extracted via the captured image. These features are combined with the weight to estimate density. This study uses 732 mangoes that are collected from several local farms. The experiment of the grading system has high accuracy with 98.3%. Instead of using Non-Destructive Testing (NDT) equipment, this grading method can be used to apply to evaluate the quality of other tropical fruits.","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"99 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using Random Forest Algorithm to Grading Mango's Quality Based on External Features Extracted from Captured Images\",\"authors\":\"Nguyen Minh Trieu, Nguyen Truong Thinh\",\"doi\":\"10.18178/joig.11.4.391-396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The grading of mango is still a manual process in agriculture. Nowadays, mangoes are classified based on human experience, which makes the grade not uniform for agricultural product export establishments. Therefore, the automated grading of mango is very important to solve these problems. In this study, a random forest algorithm is proposed for an automated mango grading system based on quality attributes such as density, surface defect, and weight. The internal features including dimensions and surface defects are extracted via the captured image. These features are combined with the weight to estimate density. This study uses 732 mangoes that are collected from several local farms. The experiment of the grading system has high accuracy with 98.3%. Instead of using Non-Destructive Testing (NDT) equipment, this grading method can be used to apply to evaluate the quality of other tropical fruits.\",\"PeriodicalId\":36336,\"journal\":{\"name\":\"中国图象图形学报\",\"volume\":\"99 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"中国图象图形学报\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.18178/joig.11.4.391-396\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"中国图象图形学报","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.18178/joig.11.4.391-396","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Using Random Forest Algorithm to Grading Mango's Quality Based on External Features Extracted from Captured Images
The grading of mango is still a manual process in agriculture. Nowadays, mangoes are classified based on human experience, which makes the grade not uniform for agricultural product export establishments. Therefore, the automated grading of mango is very important to solve these problems. In this study, a random forest algorithm is proposed for an automated mango grading system based on quality attributes such as density, surface defect, and weight. The internal features including dimensions and surface defects are extracted via the captured image. These features are combined with the weight to estimate density. This study uses 732 mangoes that are collected from several local farms. The experiment of the grading system has high accuracy with 98.3%. Instead of using Non-Destructive Testing (NDT) equipment, this grading method can be used to apply to evaluate the quality of other tropical fruits.
中国图象图形学报Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
1.20
自引率
0.00%
发文量
6776
期刊介绍:
Journal of Image and Graphics (ISSN 1006-8961, CN 11-3758/TB, CODEN ZTTXFZ) is an authoritative academic journal supervised by the Chinese Academy of Sciences and co-sponsored by the Institute of Space and Astronautical Information Innovation of the Chinese Academy of Sciences (ISIAS), the Chinese Society of Image and Graphics (CSIG), and the Beijing Institute of Applied Physics and Computational Mathematics (BIAPM). The journal integrates high-tech theories, technical methods and industrialisation of applied research results in computer image graphics, and mainly publishes innovative and high-level scientific research papers on basic and applied research in image graphics science and its closely related fields. The form of papers includes reviews, technical reports, project progress, academic news, new technology reviews, new product introduction and industrialisation research. The content covers a wide range of fields such as image analysis and recognition, image understanding and computer vision, computer graphics, virtual reality and augmented reality, system simulation, animation, etc., and theme columns are opened according to the research hotspots and cutting-edge topics.
Journal of Image and Graphics reaches a wide range of readers, including scientific and technical personnel, enterprise supervisors, and postgraduates and college students of colleges and universities engaged in the fields of national defence, military, aviation, aerospace, communications, electronics, automotive, agriculture, meteorology, environmental protection, remote sensing, mapping, oil field, construction, transportation, finance, telecommunications, education, medical care, film and television, and art.
Journal of Image and Graphics is included in many important domestic and international scientific literature database systems, including EBSCO database in the United States, JST database in Japan, Scopus database in the Netherlands, China Science and Technology Thesis Statistics and Analysis (Annual Research Report), China Science Citation Database (CSCD), China Academic Journal Network Publishing Database (CAJD), and China Academic Journal Network Publishing Database (CAJD). China Science Citation Database (CSCD), China Academic Journals Network Publishing Database (CAJD), China Academic Journal Abstracts, Chinese Science Abstracts (Series A), China Electronic Science Abstracts, Chinese Core Journals Abstracts, Chinese Academic Journals on CD-ROM, and China Academic Journals Comprehensive Evaluation Database.