This paper proposes a novel way to annotate images by leveraging search and data mining technologies based on the framework below.
The AnnoSearch system, its input is an image and a keyword which describes a concept of this image. As the above figure, the framework contains 3 stages:
1. Text-based search
Given the keyword, the system do text-based retrieval on a large-scale and high-quality Web image database and get the retrieved images.
2. Content-based search
Given the retrieved images by above text-based search, the system does content-based search to ensure the visual similarity. For scalability, this paper adopts a hash encoding algorithm.
3. Learning annotations by clustering
After finishing the above retrieval stages, the system uses an effective clustering technique called Search Result Clustering (SRC) to cluster the retrieved images and generate readable name with each cluster. The system finally annotates the given image with the names of the clusters whose scores is larger than a certain threshold.
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