Cashmere/wool identification based on bag-of-words and spatial pyramid match. Issue 21 (November 2018)

• Record Type: Journal Article
• Authors: Lu, Kai; Zhong, Yueqi; Li, Duan; Chai, Xinyu; Xie, Haoyang; Yu, Zhicai; Naveed, Tayyab
• Is Part Of: Textile research journal. Volume 88:Issue 21(2018)
• Page Start: 2435
• Page End: 2444
• Publication Date: 2018-11
• Subjects: cashmere -- wool -- identification -- image segmentation -- bag-of-words -- spatial pyramid match; Textile industry -- Periodicals; Textile fabrics -- Periodicals; Textile research -- Periodicals; Textiles et tissus -- Industrie et commerce -- Périodiques; Textiles et tissus -- Périodiques; Textiles et tissus -- Recherche -- Périodiques; Electronic journals; 677.005
• DOI: 10.1177/0040517517723027
• Languages: English
• ISSNs: 0040-5175

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.