Normalization-Cooperated Gradient Feature Extraction for Handwritten Character Recognition
TLDR
A new feature extraction approach, called normalization-cooperated gradient feature (NCGF) extraction, which maps the gradient direction elements of original image to direction planes without generating the normalized image and can be combined with various normalization methods.Abstract:
The gradient direction histogram feature has shown superior performance in character recognition. To alleviate the effect of stroke direction distortion caused by shape normalization and provide higher recognition accuracies, we propose a new feature extraction approach, called normalization-cooperated gradient feature (NCGF) extraction, which maps the gradient direction elements of original image to direction planes without generating the normalized image and can be combined with various normalization methods. Experiments on handwritten Japanese and Chinese character databases show that, compared to normalization-based gradient feature, the NCGF reduces the recognition error rate by factors ranging from 8.63 percent to 14.97 percent with high confidence of significance when combined with pseudo-two-dimensional normalization.read more
Citations
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Proceedings ArticleDOI
A Detailed Review of Feature Extraction in Image Processing Systems
TL;DR: Various types of features, feature extraction techniques and explaining in what scenario, which features extraction technique, will be better are discussed and referred in case of character recognition application.
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TL;DR: In this paper, state-of-the-art methods were evaluated on the isolated character datasets OLHWDB1.0 and HWDB-1.1 for Chinese handwriting recognition.
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Forty years of research in character and document recognition-an industrial perspective
TL;DR: An overview on the last 40-years of technical advances in the field of character and document recognition in Japan is presented, and robustness design principles, which have proven to be effective to solve complex problems in postal address recognition are discussed.
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