Jannie Fleur V. Oraño, Francis Rey F. Padao, Rhoderick D. Malangsa
{"title":"Analyzing the Accuracy of KNN-based Cacao Bean Grading System","authors":"Jannie Fleur V. Oraño, Francis Rey F. Padao, Rhoderick D. Malangsa","doi":"10.1109/HNICEM48295.2019.9072790","DOIUrl":null,"url":null,"abstract":"Cacao is one of the major crops of the tropical world and is known worldwide for its beans used for manufacturing of products which are highly popular and widely consumed around the world such as chocolate and cocoa powder. Grading the cacao beans is a method utilized by the cacao experts and farmers to ensure valuable and good supply of cacao beans in the market. However, manual grading of the cacao beans using the naked eye observation is more laborious, time consuming and less accurate. To automate the said process, a computer-based cacao beans grading system was developed using image processing and KNN algorithm. One hundred ninety (190) samples were consumed as training examples and sixty samples (60) for classification. The system was designed and developed using C# Windows Form Application as its programming language, XAMPP as its server scripting language, and MySQL as its database. The accuracy calculation of the system resulted to 93.33%, which implies that the KNN model was able to effectively grade cacao beans.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HNICEM48295.2019.9072790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Cacao is one of the major crops of the tropical world and is known worldwide for its beans used for manufacturing of products which are highly popular and widely consumed around the world such as chocolate and cocoa powder. Grading the cacao beans is a method utilized by the cacao experts and farmers to ensure valuable and good supply of cacao beans in the market. However, manual grading of the cacao beans using the naked eye observation is more laborious, time consuming and less accurate. To automate the said process, a computer-based cacao beans grading system was developed using image processing and KNN algorithm. One hundred ninety (190) samples were consumed as training examples and sixty samples (60) for classification. The system was designed and developed using C# Windows Form Application as its programming language, XAMPP as its server scripting language, and MySQL as its database. The accuracy calculation of the system resulted to 93.33%, which implies that the KNN model was able to effectively grade cacao beans.
可可是热带世界的主要作物之一,因其用于制造巧克力和可可粉等世界各地非常受欢迎和广泛消费的产品而闻名于世。可可豆分级是可可豆专家和农民使用的一种方法,以确保市场上有价值和良好的可可豆供应。然而,手工分级的可可豆使用肉眼观察更费力,耗时和准确性较低。为了实现上述过程的自动化,利用图像处理和KNN算法开发了一个基于计算机的可可豆分级系统。190个样本作为训练样本,60个样本用于分类。本系统采用c# Windows Form Application作为编程语言,XAMPP作为服务器端脚本语言,MySQL作为数据库进行设计和开发。系统的精度计算结果为93.33%,表明KNN模型能够有效地对可可豆进行分级。