Soil Color Comparison Using Munsell Soil Color Chart and Calibrated Smartphone Camera

V. Kautsar, Kuni Faizah, Arief Ika Uktoro
{"title":"Soil Color Comparison Using Munsell Soil Color Chart and Calibrated Smartphone Camera","authors":"V. Kautsar, Kuni Faizah, Arief Ika Uktoro","doi":"10.24198/jt.vol18n1.3","DOIUrl":null,"url":null,"abstract":"Soil color is a crucial property in soil fertility assessment and monitoring. However, the subjective nature of the Munsell Soil Color Chart (MSCC) can lead to uncertainty in the analysis. To address this issue, a study was conducted to develop a soil color classification model from smartphone digital imagery based on color analysis and MSCC. The study involved taking 26 soil samples from various soil types and locations in the Special Region of Yogyakarta, Indonesia. Digital images of the soil were taken through a smartphone camera and compared with observations using MSCC to compare color differences (ΔE) based on Lab values. Soil images obtained from indoor studio conditions and calibration using spydercheckr in indoor and outdoor conditions are compared with MSCC and Chromameter values. The L*a*b color space was found to be superior to RGB for predicting and detecting small differences in color. The study also found that the Munsell soil color chart (MSCC) had a lower color difference than the chromameter in all lighting conditions, indicating that the MSCC or visual assessment can better detect the main soil color or soil matrix, while chromameter readings may have errors due to soil impurities.","PeriodicalId":229622,"journal":{"name":"Jurnal Teknotan","volume":"11 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Teknotan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24198/jt.vol18n1.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Soil color is a crucial property in soil fertility assessment and monitoring. However, the subjective nature of the Munsell Soil Color Chart (MSCC) can lead to uncertainty in the analysis. To address this issue, a study was conducted to develop a soil color classification model from smartphone digital imagery based on color analysis and MSCC. The study involved taking 26 soil samples from various soil types and locations in the Special Region of Yogyakarta, Indonesia. Digital images of the soil were taken through a smartphone camera and compared with observations using MSCC to compare color differences (ΔE) based on Lab values. Soil images obtained from indoor studio conditions and calibration using spydercheckr in indoor and outdoor conditions are compared with MSCC and Chromameter values. The L*a*b color space was found to be superior to RGB for predicting and detecting small differences in color. The study also found that the Munsell soil color chart (MSCC) had a lower color difference than the chromameter in all lighting conditions, indicating that the MSCC or visual assessment can better detect the main soil color or soil matrix, while chromameter readings may have errors due to soil impurities.
使用 Munsell 土壤颜色表和校准过的智能手机摄像头进行土壤颜色比较
土壤颜色是土壤肥力评估和监测中的一个重要属性。然而,芒塞尔土壤色图(MSCC)的主观性会导致分析的不确定性。为了解决这个问题,我们开展了一项研究,根据颜色分析和 MSCC,从智能手机数字图像中开发土壤颜色分类模型。研究从印度尼西亚日惹特区的不同土壤类型和地点采集了 26 个土壤样本。通过智能手机摄像头拍摄了土壤的数字图像,并使用 MSCC 与观察结果进行比较,以比较基于 Lab 值的颜色差异 (ΔE)。在室内工作室条件下获得的土壤图像以及在室内和室外条件下使用 spydercheckr 进行的校准与 MSCC 和 Chromameter 值进行了比较。结果发现,在预测和检测颜色的微小差异方面,L*a*b 色彩空间优于 RGB。研究还发现,在所有光照条件下,芒塞尔土壤色图(MSCC)的色差都低于色度计,这表明 MSCC 或目测评估能更好地检测主要土壤颜色或土壤基质,而色度计读数可能会因土壤杂质而产生误差。
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
自引率
0.00%
发文量
0
×
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