Title :
Google image search refinement: Finding text in images using local features
Author :
Zhou, Yi ; Chen, Kai ; Yang, Xiaokang
Author_Institution :
Dept. of Electron. Eng., Shanghai Jiaotong Univ., Shanghai, China
Abstract :
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.
Keywords :
Internet; computational geometry; feature extraction; image matching; image retrieval; natural language processing; optical character recognition; search engines; text analysis; transforms; Chinese characters images; Google image search refinement; MPLSH; SIFT feature matching; Web image search; character recognition; geometric verification algorithm; local feature utilization; query-text SDB; scale invariant feature transform; text recognition; text-based image search; Buildings; Feature extraction; Google; Graphics processing unit; Image recognition; Layout; Text recognition; Character Recognition; Local Feature; Natural Images;
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2012 IEEE International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-1-4673-0088-9
DOI :
10.1109/CSAE.2012.6272557
