Abstract:

An automatic image annotation method based on weighted feature is proposed. Firstly, a weighted feature clustering algorithm is employed on the semantic concept clusters of the image regions. For a given cluster, we determine relevant features based on their statistical distribution and assign greater weights to relevant features as compared to less relevant features．In this way the computing of clustering algorithm can avoid dominated by trivial relevant or irrelevant features. Then, the relationship between clustering regions and semantic concepts is established according to the labeled images in the training set. Under the condition of the new unlabeled image regions, we calculate the conditional probability of each semantic keyword and annotate the new images with maximal conditional probability. Experiments on the Corel image set show the effectiveness of the new algorithm.

Key words: weighted feature, automatic image annotation, clustering