TY - GEN
T1 - Character recognition in natural scene images using local description
AU - Zhang, Boyu
AU - Zhao, Wei
AU - Liu, Jia Feng
AU - Wu, Rui
AU - Tang, Xiang Long
PY - 2012
Y1 - 2012
N2 - Text information extracted from scene images is often the key clue for better performance of scene understanding and image retrieval. However, the clutter background and variations, which are intrinsic in scene images, make the natural scene character recognition task rather complicated. To overcome these disadvantages, we propose a novel approach for character recognition task in natural scene images. In the method, character classes are described by groups of local features using a probabilistic model. Structures of characters are represented by mutual positions of local features. For model learning, parameter estimating is done through expectation-maximization in a weak-supervised manner. Experiment results over datasets which includes both synthetic and authentic data demonstrate the validity of the approach.
AB - Text information extracted from scene images is often the key clue for better performance of scene understanding and image retrieval. However, the clutter background and variations, which are intrinsic in scene images, make the natural scene character recognition task rather complicated. To overcome these disadvantages, we propose a novel approach for character recognition task in natural scene images. In the method, character classes are described by groups of local features using a probabilistic model. Structures of characters are represented by mutual positions of local features. For model learning, parameter estimating is done through expectation-maximization in a weak-supervised manner. Experiment results over datasets which includes both synthetic and authentic data demonstrate the validity of the approach.
KW - Gaussian Mixture Model
KW - character recognition
KW - expectation maximization
KW - local description
KW - natural scene images
UR - https://www.scopus.com/pages/publications/84865815052
U2 - 10.1007/978-3-642-31919-8_25
DO - 10.1007/978-3-642-31919-8_25
M3 - 会议稿件
AN - SCOPUS:84865815052
SN - 9783642319181
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 193
EP - 200
BT - Intelligent Science and Intelligent Data Engineering - Second Sino-Foreign-Interchange Workshop, IScIDE 2011, Revised Selected Papers
T2 - 2nd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2011
Y2 - 23 October 2011 through 25 October 2011
ER -