Christian Bhennz Soriano, Didric Kirsten Ferrer, J. Villaverde, Dionis A. Padilla
{"title":"Classification of Citrus Sinensis Peel for Production of Biopolymers Using Probability Distribution Function","authors":"Christian Bhennz Soriano, Didric Kirsten Ferrer, J. Villaverde, Dionis A. Padilla","doi":"10.1109/ICCSSE52761.2021.9545158","DOIUrl":null,"url":null,"abstract":"Citrus Sinensis, a citrus fruit commonly known as sweet orange that, when processed at a small scale or industrial level, produces a massive amount of waste after processing. Over the years, citrus peels that are rejected for exports are used as natural fertilizers with the benefit of minimizing citrus peel waste. The methods used to reduce waste in this industry remain inadequate. This study introduces an environmentally safe approach that utilizes peels from rejected oranges for biopolymers. The objective of the study is to create a system that will capture the surface color of oranges and classify if the fruit can be used for extraction of biopolymer using image processing by converting the RGB image to HSV color space in OpenCV. The probability distribution function method was used as a basis for color classification and produced an accuracy of 92%.","PeriodicalId":143697,"journal":{"name":"2021 IEEE 7th International Conference on Control Science and Systems Engineering (ICCSSE)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 7th International Conference on Control Science and Systems Engineering (ICCSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSSE52761.2021.9545158","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Citrus Sinensis, a citrus fruit commonly known as sweet orange that, when processed at a small scale or industrial level, produces a massive amount of waste after processing. Over the years, citrus peels that are rejected for exports are used as natural fertilizers with the benefit of minimizing citrus peel waste. The methods used to reduce waste in this industry remain inadequate. This study introduces an environmentally safe approach that utilizes peels from rejected oranges for biopolymers. The objective of the study is to create a system that will capture the surface color of oranges and classify if the fruit can be used for extraction of biopolymer using image processing by converting the RGB image to HSV color space in OpenCV. The probability distribution function method was used as a basis for color classification and produced an accuracy of 92%.