DocumentCode :
703662
Title :
Feature extraction of clothing texture patterns for classification
Author :
Chaitra, G.N. ; Khare, Nayan
Author_Institution :
Dept. of CSE, Christ Univ., Bangalore, India
fYear :
2015
fDate :
8-10 Jan. 2015
Firstpage :
6
Lastpage :
9
Abstract :
Different features are extracted for Pattern Recognition using an efficient algorithms like Scale Invariant Feature Transform, Rotation invariant Radon Transform and extracting statistical features of a texture image. Support vector machine with RBF kernel in Weka is used in this paper for classification. This paper shows method to classify the clothing texture patterns like strips, plaid, pattern less and irregular pattern. This paper also proposes a method which can be efficient method to apply for the real time natural texture patterns and colors recognition systems. This paper gives the experiments results and the proposed method to enhance the experiments accuracy in future scope.
Keywords :
Radon transforms; clothing; feature extraction; image classification; image colour analysis; image recognition; image texture; radial basis function networks; statistical analysis; support vector machines; RBF kernel; Weka; clothing texture patterns; colors recognition system; image texture; pattern classification; pattern recognition; rotation invariant radon transform; scale invariant feature transform; statistical feature extraction; support vector machine; Accuracy; Clothing; Entropy; Feature extraction; Market research; Pattern recognition; Transforms; Feature descriptors; Radon transform variance; Support Vector Machine; classification; statistical analysis; texture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recent and Emerging trends in Computer and Computational Sciences (RETCOMP), 2015
Conference_Location :
Bangalore
Print_ISBN :
978-1-4799-1834-8
Type :
conf
DOI :
10.1109/RETCOMP.2015.7090796
Filename :
7090796
Link To Document :
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