Abstract In order to improve the retrieval performance of images, this paper proposes an efficient approach for extracting and retrieving color images. The block diagram of our proposed approach to content-based image retrieval (CBIR) is given firstly, and then we introduce three image feature extracting arithmetic including color histogram, edge histogram and edge direction histogram, the histogram Euclidean distance, cosine distance and histogram intersection are used to measure the image level similarity. On the basis of using color and texture features separately, a new method for image retrieval using combined features is proposed. With the test for an image database including 766 general-purpose images and comparison and analysis of performance evaluation for features and similarity measures, our proposed retrieval approach demonstrates a promising performance. Experiment shows that combined features are superior to every single one of the three features in retrieval.
[1]
Robert M. Gray,et al.
Image retrieval using color histograms generated by Gauss mixture vector quantization
,
2004,
Comput. Vis. Image Underst..
[2]
Timothy K. Shih,et al.
An Intelligent Content-based Image Retrieval System Based on Color, Shape and Spatial Relations
,
2001
.
[3]
Syungog An,et al.
Image Indexing Based On Mpeg-7 Scalable Color Descriptor
,
2004
.
[4]
B. S. Manjunath,et al.
Color and texture descriptors
,
2001,
IEEE Trans. Circuits Syst. Video Technol..
[5]
Shih-Fu Chang,et al.
Tools and techniques for color image retrieval
,
1996,
Electronic Imaging.
[6]
Shih-Fu Chang,et al.
Image Retrieval: Current Techniques, Promising Directions, and Open Issues
,
1999,
J. Vis. Commun. Image Represent..