A framework for image retrieval with hybrid features
Jiayin Kang, Wenjuan Zhang · 2012
Image retrieval is an active research area in image processing, pattern recognition, and computer vision. This paper presented a framework in content-based image retrieval (CBIR) by combining the color, texture and shape features. Firstly, transforming color space from RGB model to HSI model, and then extracting color histogram to form color feature vector. Secondly, extracting the texture feature by using gray co-occurrence matrix. Thirdly, applying Zernike moments to extract the shape features. Finally, combining the color, texture and shape features to form the fused feature vectors of entire image. Experiments on commonly used image datasets show that the proposed scheme achieves a very good performance in terms of the precision, recall compared with other methods.