Authors:
Gang Gu
;
Jiangqin Wu
;
Tianjiao Mao
and
Pengcheng Gao
Affiliation:
Zhejiang University, China
Keyword(s):
GIST-SIFT-SSC, Image Understanding, Chinese Characters Recognition, Mobile Platform.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Digital Photography
;
Document Imaging in Business
Abstract:
Chinese characters are profound and polysemantic. Reading a Chinese character is a procedure of image understanding, if the Chinese character is captured as an image. Due to the complexity of structure and plenty of Chinese characters, there always exist some unfamiliar characters when reading books, so it would be great if a tool is provided to help users understand the meaning of unknown characters. We propose a method that combines global and local features(i.e., GIST and SIFT features) to recognize the Chinese character images captured from mobile camera. Three schemes are investigated based on practical considerations. Firstly,the so-called GIST and SIFT descriptors extracted from Chinese character images are adopted purely as features. Then filter the SIFT feature points of similar Chinese character images based on GIST feature. Finally, compress the storage of GIST and SIFT descriptors to accommodate mobile platform with Similarity Sensitive Coding(SSC) algorithm. At the stag
e of recognition, the top 2k Chinese characters are firstly obtained by hamming distance in GIST feature space, then reorder the selected characters as final result by SIFT feature. We build an Android app that implements the recognition algorithm. Experiment shows satisfying recognition results of our proposed application compared to other Android apps.
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