In:
Textile Research Journal, SAGE Publications, Vol. 88, No. 21 ( 2018-11), p. 2435-2444
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
0040-5175
,
1746-7748
DOI:
10.1177/0040517517723027
Language:
English
Publisher:
SAGE Publications
Publication Date:
2018
detail.hit.zdb_id:
2209596-2
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