A new method of printed fabric image retrieval based on color moments and gist feature description

Image retrieval has been an active research topic in recent decades. In this paper, a novel and effective algorithm is proposed for printed fabric image retrieval by combining color moments methods and gist feature description methods. Color information distribution could be declared by color moments very well and gist feature description has an advantage in representation of spatial information. Therefore, color features and spatial information features are respectively extracted by color moments and the gist feature description method, which constitutes a feature database. After that, the similarity between query image features and the feature database is computed by Euclidean distance. To demonstrate the efficacy of the framework, experiments are conducted on the FABRIC database. Experimental results indicate that the proposed algorithm is more effective and accurate than other hybrid schemes for printed fabric images, in terms of precision and recall.