Department of Textile Engineering, Faculty of Engineering, Yazd University
Abstract
Nowadays, the fashion industry is a global industry in which most countries invest in it. In recent years by development of e-commerce and its time saving and providing wide selection of goods for customers, many people do their purchasing through online shops instead of going to stores. So for the online apparel markets, it is necessary to have a system to retrieve garment images and include them in a specific database, so to do searching quicker and more effectively. In this way customers find it easier to have access what they look for. Although it is simple to detect a garment style by image searching but it is no so for a computer system. In this paper an algorithm is presented which is based on image processing and K-means clustering for grouping the garment images. The algorithm has the ability to group similar garment images. The results show that this developed system can detect and cluster 67% of database images correctly.
Zarenejad, Z., & Payvandy, P. (2013). Garment Images Clustering Based on Image Processing Techniques and K-Means Algorithm. Journal of Textile Science and Technology, 3(1), 3-10.
MLA
Z. Zarenejad; P. Payvandy. "Garment Images Clustering Based on Image Processing Techniques and K-Means Algorithm". Journal of Textile Science and Technology, 3, 1, 2013, 3-10.
HARVARD
Zarenejad, Z., Payvandy, P. (2013). 'Garment Images Clustering Based on Image Processing Techniques and K-Means Algorithm', Journal of Textile Science and Technology, 3(1), pp. 3-10.
VANCOUVER
Zarenejad, Z., Payvandy, P. Garment Images Clustering Based on Image Processing Techniques and K-Means Algorithm. Journal of Textile Science and Technology, 2013; 3(1): 3-10.
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