An Efficient and Effective Similarity Measure to Enable Data Mining of Fabric Image of Xinjiang Folk Art

Abstract

Fabric pattern is a folk art of artificial fabrics pattern design which includes apparels (known as clothes and hats), and crafts (known as carpets and tapestries). Although image processing, information retrieval and data mining have made a large impact on many human endeavors, they never had an impact on the study of the fabric image. In this paper we will present the reasons for this, and introduce a novel similarity measure and algorithm (Pattern Similarity Measuring Algorithm (PSMA)) which allows efficient data mining for large collections of fabric image. PSMA, the effectiveness of which is proved be experiment test, is an image similarity measurement algorithm that achieves the machine-learning based theory via the gradient descent algorithm with multidimensional linear regression.

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Cite this paper

@inproceedings{Te2015AnEA, title={An Efficient and Effective Similarity Measure to Enable Data Mining of Fabric Image of Xinjiang Folk Art}, author={Rigen Te and Xiongfei Li and Yueying Zhang}, year={2015} }