Google image search refinement: Finding text in images using local features

In this paper, we implement a Google image search refinement that utilizes local features to find Chinese characters in search results, including following stages: (1) Chinese characters images and their SIFT features (SDB) are generated offline, (2) A text-based image search results are retrieved from the Google, (3) SIFT features of results are matched to query-text SDB using MPLSH, (4) A geometric verification algorithm is used to find the query-text and rerank results. Experiment results show that our approach is simple and effective in recognition of text in natural images, and is helpful to refine the web image search.

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