An automatic image annotation method based on the mutual K-nearest neighbor graph

In order to improve the accuracy of the image annotation, an automatic image annotation method based on mutual K-nearest neighbor graph (MKNN) is proposed. The proposed algorithm describes the relationship between low-level features, annotation words and image by a mutual K-nearest neighbor graph. Semantic information is extracted by exploiting the mutual relationship of two nodes in the mutual K-nearest neighbor graph. Inverse document frequency (IDF) is introduced to adjust the weights of edges between the image node and its annotation word´s node, which overcomes the deviation caused by high-frequency words. Experimental results in Corel image dataset show that the proposed algorithm improves effectively the image annotation performance..