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MARKET SEGMENTATION USING COLOR INFORMATION OF IMAGES

International Journal of Electronic Commerce Studies

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Field Value
 
Title MARKET SEGMENTATION USING COLOR INFORMATION OF IMAGES
 
Creator Daniel, Ines; Brandenburg University of Technology
Frost, Sarah; Brandenburg University of Technology
Baier, Daniel; Brandenburg University of Technology
 
Subject Color Space; Image Clustering; Market Segmentation
 
Description Market segmentation is an important area of marketing. In this field, researchers use clustering algorithms to divide customers into homogeneous groups. Traditionally, these groups are formed on the basis of survey data. In these surveys, the test persons often have to answer a variety of questions. With the increasing amount of digitalization and improved technical capabilities, new databases are now available for this purpose. For example, potential customers might provide photos that describe their activities, interests, or opinions. In the area of content-based image retrieval (CBIR) there are various methods that currently exist to analyze the similarity of such photos, e.g., using distributional descriptors of colors, textures, or shapes. In this paper we discuss which dissimilarity measures could be used to segment photos by hierarchical clustering on the basis of color. For this purpose we analyzed 2,100 images concerning three color spaces RGB, HSV and CIE L*a*b* using different distance measures as the basis for hierarchical clustering.To cite this document: Ines Daniel, Sarah Frost, and Daniel Baier, "Market segmentation using color information of images", International Journal of Electronic Commerce Studies, Vol.6, No.1, pp.137-144, 2015.Permanent link to this document:http://dx.doi.org/10.7903/ijecs.1400
 
Publisher Academy of Taiwan Information Systems Research
 
Contributor This research is funded by Federal Ministry for Education and Research under grants 03FO3072. The authors are responsible for the content of this paper.
 
Date 2015-04-26
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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Format application/pdf
 
Identifier http://academic-pub.org/ojs/index.php/ijecs/article/view/1400
 
Source International Journal of Electronic Commerce Studies; Vol 6, No 1 (2015); 137-144
2073-9729
 
Language eng
 
Relation http://academic-pub.org/ojs/index.php/ijecs/article/view/1400/287
 
Rights Copyright (c) 2015 International Journal of Electronic Commerce Studies