Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/31072
Title: Identification of handloom and powerloom fabrics using proximal support vector machines
Authors: Ghosh, Anindya
Guha, Tarit
Bhar, R B
Keywords: Handloom fabrics;Image processing;Pattern classification;Proximal support vector machine;Powerloom fabrics
Issue Date: Mar-2015
Publisher: NISCAIR-CSIR, India
Abstract: This study endeavors to recognize handloom and powerloom products by means of proximal support vector machine (PSVM) using the features extracted from gray level images of both fabrics. A k-fold cross validation technique has been applied to assess the accuracy. The robustness, speed of execution, proven accuracy coupled with simplicity in algorithm hold the PSVM as a foremost classifier to recognize handloom and powerloom fabrics.
Page(s): 87-93
URI: http://hdl.handle.net/123456789/31072
ISSN: 0975-1025 (Online); 0971-0426 (Print)
Appears in Collections:IJFTR Vol.40(1) [March 2015]

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