Image retrieval based on gradient texton coherence vector
基于梯度基元聚合矢量的图像检索算法*

This paper proposed a new image retrieval algorithm based on gradient texton coherence vector for fusion of multi-features. The algorithm computed the edge gradient first in the modified HSV color space, and then gained gradient texton map by scanning the gradient image through the special texton types. The texton pixels were combined into the coherence set, the other pixels were the non-coherence set. At last,it represented the feature vector of the image retrieval by color auto-correlogram in two sets, and realized the image retrieval based multi-features which fused color, shape, texture and spatial information. Experimental results show that the proposed algorithm can combine color, texture, shape and spatial characteristic effectively, and have valid precision and recall.