Document image analysis
Object Matching Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Characters in Scene Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Structural Rectification of Non-planar Document Images: Application to Graphics Recognition
GREC '01 Selected Papers from the Fourth International Workshop on Graphics Recognition Algorithms and Applications
Document Image De-warping for Text/Graphics Recognition
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
A framework for recognition books on bookshelves
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Robust chinese character recognition by selection of binary-based and grayscale-based classifier
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
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This paper presents a multiple-dictionary method for recognizing low-quality characters in scene images. First, the environmental conditions of an input image are estimated using an initial dictionary. Then, a relevant dictionary from multiple dictionaries reflecting different environmental conditions is automatically selected from the estimation and used for recognition. Experiments are made for characters in images of bookshelves. The results show that the proposed method achieves a higher recognition rate (89.8%) than that obtained by using a single dictionary (76.4%). Furthermore, recognition accuracy improves from 89.8% to 95.2% using contextual postprocessing.