Image analysis – Pattern recognition – Template matching
Reexamination Certificate
2007-02-06
2007-02-06
Mancuso, Joseph (Department: 2624)
Image analysis
Pattern recognition
Template matching
Reexamination Certificate
active
10444315
ABSTRACT:
In a method for character recognition based on Gabor filter group the Gabor filter's joint spatial/spatial-frequency localization and capability to efficiently extract characters' local structural features are employed to extract, from the character image, information of the stroke direction of characters as the recognition information of characters, so as to improve the capability to resist the noises, backgrounds, brightness variances in images and the deformation of characters. Using this information, a simple and effective parameter design method is put forward to optimally design the Gabor filter, ensuring a preferable recognition performance; a corrected Sigmoid function is used to non-linearly adaptively process the stroke direction information output from the Gabor filter group. When extracting the feature from blocks, Gaussian filter array is used to process the positive and negative values output from Gabor filter group to enhance the discrimination ability of the extracted features.
REFERENCES:
patent: 5164992 (1992-11-01), Turk et al.
Hamamoto, “Recogntion of Handwritten Numerals using Gabor Features,” 1996, IEEE.
Kuo, “A Radical-Partitioned Neural Network System Using a Modified Sigmoid Function and a Weight-Dotted Radical Selector for Large-Volume Chinese Characters Recognition VLSI,” 1994, IEEE.
Wang, “Optimized Gabor Filter Based Feature Extraction for Character Recognition,” 2002, IEEE.
Hamamoto, “Recognition of Handprinted Chinese Characters using Gabor Features,” 1995, IEEE.
Ding Xiaoqing
Fang Chi
Liu Changsong
Peng Liangrui
Wang Xuewen
Liew Alex
Mancuso Joseph
RatnerPrestia
Tsinghua University
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