Cashmere/wool identification based on bag-of-words and spatial pyramid match

Due to the similarities between cashmere and wool, the automatic identification of these two animal fibers continues to be a huge challenge in textile society. In this paper, for the identification of micrographs of cashmere and wool, bag-of-words and spatial pyramid matching are used. Each fiber im...

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Bibliographic Details
Published in:Textile research journal 2018-11, Vol.88 (21), p.2435-2444
Main Authors: Lu, Kai, Zhong, Yueqi, Li, Duan, Chai, Xinyu, Xie, Haoyang, Yu, Zhicai, Naveed, Tayyab
Format: Article
Language:English
Subjects:
Animal fibers
Cashmere
Classification
Feature extraction
Fibers
Identification
Image classification
Image enhancement
Image processing
Image segmentation
Materials research
Photomicrographs
Support vector machines
Wool
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Summary:Due to the similarities between cashmere and wool, the automatic identification of these two animal fibers continues to be a huge challenge in textile society. In this paper, for the identification of micrographs of cashmere and wool, bag-of-words and spatial pyramid matching are used. Each fiber image was regarded as a collection of feature vectors in our logic. The vectors, extracted from the original dataset, were fed into a support vector machine for supervised classification. The codebook size and the resolution level were completely investigated. The experimental results indicated that the image segmentation delivered a positive contribution in enhancing the accuracy of classification. The overall performance of the model was robust under various blend ratios. It verifies that the bag-of-words with spatial pyramid match is an effective approach to the identification of cashmere and wool fibers.
ISSN:0040-5175
1746-7748
DOI:10.1177/0040517517723027