With the prevalence of digital cameras, more and more people have considerable digital images on their personal devices. As a result, there are increasing needs to effectively search these personal images. Automatic image annotation may serve the goal, for the annotated keywords could facilitate the search processes. Although many image annotation methods have been proposed in recent years, their effectiveness on arbitrary personal images is constrained by their limited scalability, i.e. limited lexicon of small-scale training set. To be scalable, we propose a searchbased image annotation (SBIA) algorithm that is analogous to Web page search. First, content-based image retrieval (CBIR) technology is used to retrieve a set of visually similar images from a large-scale Web image set. Then, a text-based keyword search (TBKS) technique is used to obtain a ranked list of candidate annotations for each retrieved image. Finally, a fusion algorithm is used to combine the ranked lists into the...