Searching images in a textile image database

Abstract

In this paper, a textile image search system is proposed to query similar textile images in an image database. Five feature descriptors about the color, texture, and shape defined in the MPEG-7 specification, which are relevant to textile image characteristics, are extracted from a dataset. First, we tune the feature weights using a genetic algorithm, based on a predefined training dataset. Then, for each extracted feature descriptor, we use K-means to partition it into four clusters and combine them together to obtain an MPEG-7 signature. Finally, when users input a query image, the system finds out similar images by combining the results based on MPEG-7 signatures and the ones in three nearest classes. The experimental results show that the similar images returned from an image database to a query textile image are acceptable for humans and with good quality.