A Color Reflectance Model And Its Use For Segmentation

G. Healey
{"title":"A Color Reflectance Model And Its Use For Segmentation","authors":"G. Healey","doi":"10.1109/CCV.1988.590024","DOIUrl":null,"url":null,"abstract":"This paper presents a color reflectance model and demonstrates its usefulness for segn~entation. I adopt general physical models which describe the interaction of light with matter. These models apply to both metal and dielectric materials. The models indicate that, in general, reflectance is a complicated function of waveleiigth and geometry. An analysis of the general reflectance models, however, shows that approximate reAectance models exist which preserve much of the structure of the more detailed models. The approximate color reflectance model is the basis of an algorithm which is used during segmentation. This algorithm uses normalized color to classify surfaces according to milr terial composition. Experimen ta1,results are presented. electrics, ACRM is equivalent to the dichromatic reflection model suggested by Shafer [14]. In this paper, I use the Reichman body scattering model [13] to show that the dichromatic reflection model is a reasonable approximation for a large class of inhomogeneous dielectrics. I also show from the Torrance-Sparrow [17] specular reflection model and the Fresnel equations [2] that a unichromatic reflection model is a reasonable approximation for metals. Thus, ACRM combines the dichromatic reflection model for inhomogeneous dielectrics with a unichromatic reflection model for metals. The analysis includes an estimate of the accuracy of ACRM for various materials. An algorithm is derived from ACRM which is used to classify image regions based on the material of the corresponding object surfaces.","PeriodicalId":229545,"journal":{"name":"[1988 Proceedings] Second International Conference on Computer Vision","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1988 Proceedings] Second International Conference on Computer Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCV.1988.590024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

This paper presents a color reflectance model and demonstrates its usefulness for segn~entation. I adopt general physical models which describe the interaction of light with matter. These models apply to both metal and dielectric materials. The models indicate that, in general, reflectance is a complicated function of waveleiigth and geometry. An analysis of the general reflectance models, however, shows that approximate reAectance models exist which preserve much of the structure of the more detailed models. The approximate color reflectance model is the basis of an algorithm which is used during segmentation. This algorithm uses normalized color to classify surfaces according to milr terial composition. Experimen ta1,results are presented. electrics, ACRM is equivalent to the dichromatic reflection model suggested by Shafer [14]. In this paper, I use the Reichman body scattering model [13] to show that the dichromatic reflection model is a reasonable approximation for a large class of inhomogeneous dielectrics. I also show from the Torrance-Sparrow [17] specular reflection model and the Fresnel equations [2] that a unichromatic reflection model is a reasonable approximation for metals. Thus, ACRM combines the dichromatic reflection model for inhomogeneous dielectrics with a unichromatic reflection model for metals. The analysis includes an estimate of the accuracy of ACRM for various materials. An algorithm is derived from ACRM which is used to classify image regions based on the material of the corresponding object surfaces.
颜色反射率模型及其在分割中的应用
本文提出了一种颜色反射率模型,并证明了它在分割中的实用性。我采用一般的物理模型来描述光与物质的相互作用。这些模型适用于金属和介电材料。模型表明,一般来说,反射率是波长和几何的复杂函数。然而,对一般反射率模型的分析表明,存在近似的反射率模型,这些模型保留了更详细模型的大部分结构。近似颜色反射率模型是分割算法的基础。该算法采用归一化颜色,根据材料组成对表面进行分类。给出了实验结果。在电学上,ACRM相当于Shafer[14]提出的二色反射模型。在本文中,我使用Reichman体散射模型[13]来表明二色反射模型是一种合理的近似,适用于大类别的非均匀介质。我还从Torrance-Sparrow[17]镜面反射模型和菲涅耳方程[2]中表明,单色反射模型是金属的合理近似。因此,ACRM结合了非均匀介质的二色反射模型和金属的单色反射模型。分析包括对各种材料的ACRM精度的估计。在ACRM的基础上提出了一种基于物体表面材质对图像区域进行分类的算法。
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:604180095
Book学术官方微信