Segmentasi Daun Cendana Berbasis Citra Menggunakan Otsu Thresholding

IF 2.4 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
P. G. Manek, Budiman Baso, Kristoforus Fallo, Risald Risald, Hevi Herlina Ullu
{"title":"Segmentasi Daun Cendana Berbasis Citra Menggunakan Otsu Thresholding","authors":"P. G. Manek, Budiman Baso, Kristoforus Fallo, Risald Risald, Hevi Herlina Ullu","doi":"10.32938/jitu.v3i1.3868","DOIUrl":null,"url":null,"abstract":"The segmentation process is the separation of parts of the object area from the background in an image, so that segmented objects can be processed for other purposes such as pattern recognition. The results of segmentation must be accurate, if it is not accurate in separating objects in the image it will affect the results of further processing. The segmentation process is carried out using the Otsu Thresholding method on sandalwood leaf images by first applying the Median filter to reduce noise. After obtaining the segmented image, then performing performance measurements. The segmentation results from each test are evaluated using the RAE (relative foreground area error) and ME (misclassification error). The segmentation results of 8 sandalwood leaf images from 2 existing conditions show that, sandalwood leaf image segmentation with good leaf conditions obtains the best segmentation results with smaller errors of 5 image data. While the images of sandalwood leaves affected by the disease as many as 3 image data have more diverse areas so that the segmentation results are not good without any morphological process","PeriodicalId":51872,"journal":{"name":"International Journal of Information and Learning Technology","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Information and Learning Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32938/jitu.v3i1.3868","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

The segmentation process is the separation of parts of the object area from the background in an image, so that segmented objects can be processed for other purposes such as pattern recognition. The results of segmentation must be accurate, if it is not accurate in separating objects in the image it will affect the results of further processing. The segmentation process is carried out using the Otsu Thresholding method on sandalwood leaf images by first applying the Median filter to reduce noise. After obtaining the segmented image, then performing performance measurements. The segmentation results from each test are evaluated using the RAE (relative foreground area error) and ME (misclassification error). The segmentation results of 8 sandalwood leaf images from 2 existing conditions show that, sandalwood leaf image segmentation with good leaf conditions obtains the best segmentation results with smaller errors of 5 image data. While the images of sandalwood leaves affected by the disease as many as 3 image data have more diverse areas so that the segmentation results are not good without any morphological process
使用大辅乳分割以香橼为基础的图像
分割过程是将图像中目标区域的部分与背景分离,以便对分割后的对象进行处理,用于其他目的,如模式识别。分割的结果必须是准确的,如果对图像中物体的分割不准确,就会影响进一步处理的结果。首先对檀香叶图像进行中值滤波去噪,然后采用Otsu阈值分割方法对檀香叶图像进行分割。得到分割后的图像后,进行性能测量。使用RAE(相对前景区域误差)和ME(误分类误差)对每个测试的分割结果进行评估。对现有2种条件下8张檀香叶图像的分割结果表明,叶片条件较好的檀香叶图像分割得到5张图像数据的最佳分割结果,且误差较小。而檀香病叶图像多达3张图像数据,区域较为多样化,没有经过形态学处理,分割效果不佳
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
International Journal of Information and Learning Technology
International Journal of Information and Learning Technology COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
6.10
自引率
3.30%
发文量
33
期刊介绍: International Journal of Information and Learning Technology (IJILT) provides a forum for the sharing of the latest theories, applications, and services related to planning, developing, managing, using, and evaluating information technologies in administrative, academic, and library computing, as well as other educational technologies. Submissions can include research: -Illustrating and critiquing educational technologies -New uses of technology in education -Issue-or results-focused case studies detailing examples of technology applications in higher education -In-depth analyses of the latest theories, applications and services in the field The journal provides wide-ranging and independent coverage of the management, use and integration of information resources and learning technologies.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信