期刊名称：International Journal of Image, Graphics and Signal Processing
印刷版ISSN：2074-9074
电子版ISSN：2074-9082
出版年度：2019
卷号：11
期号：1
页码：54-61
DOI：10.5815/ijigsp.2019.01.06
出版社：MECS Publisher
摘要：The proposed work gives a comparative study of three different classifiers, namely, decision tree (DT), support vector machine (SVM) and artificial neural network (ANN) for variety classification of certain thin and thick fabric images. The textural features are used in the work. The overall classification rates of 85%, 86% and 94% are obtained for DT, SVM and ANN classifiers respectively. Better results for varieties of thick fabric images are obtained compared to the varieties of thin fabric images. Further, the ANN classifier has given good classification rate than DT and SVM classifiers. But, it is also observed that, DT classifier gives better results in case of varieties of thick fabric images. The work finds applications in apparel industry, cost estimation, setting the washing time, fashion design etc.
