Edwin R. Arboleda, Arnel C. Fajardo, Ruji P. Medina
{"title":"An image processing technique for coffee black beans identification","authors":"Edwin R. Arboleda, Arnel C. Fajardo, Ruji P. Medina","doi":"10.1109/ICIRD.2018.8376325","DOIUrl":null,"url":null,"abstract":"The quality of a coffee bean is determined by several factors including color, texture, and size. High quality beans are carefully refined where defects, such as black beans, are removed. The assessment through visual inspection may be subjected to external factors such as light and the amount of beans to be inspected. This study presents a method of controlling the coffee bean quality using Image Processing techniques. Normal beans are identified through the extraction of RGB color components of training image. The RGB values were integrated in an image processing technique that eliminated the black beans in the image. Using the technique in this study, a classification of 100% were achieved for eliminating the black beans in the testing images.","PeriodicalId":397098,"journal":{"name":"2018 IEEE International Conference on Innovative Research and Development (ICIRD)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"51","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Innovative Research and Development (ICIRD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIRD.2018.8376325","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 51
Abstract
The quality of a coffee bean is determined by several factors including color, texture, and size. High quality beans are carefully refined where defects, such as black beans, are removed. The assessment through visual inspection may be subjected to external factors such as light and the amount of beans to be inspected. This study presents a method of controlling the coffee bean quality using Image Processing techniques. Normal beans are identified through the extraction of RGB color components of training image. The RGB values were integrated in an image processing technique that eliminated the black beans in the image. Using the technique in this study, a classification of 100% were achieved for eliminating the black beans in the testing images.