DocumentCode :
3181840
Title :
An impact of ridgelet transform in handwritten recognition: A study on very large dataset of Kannada script
Author :
Naveena, C. ; Aradhya, V. N Manjunath
Author_Institution :
Dept. of Inf. Sci. & Eng., Dayananda Sagar Coll. of Eng., Bangalore, India
fYear :
2011
fDate :
11-14 Dec. 2011
Firstpage :
618
Lastpage :
621
Abstract :
Handwritten character recognition is a difficult problem due to the great variations on writing styles, different size and orientation angle of the characters. In this paper, we propose an unconstrained handwritten Kannada character recognition based on the ridgelet transforms. Ridglets are a powerful instrument in catching and representing mono-dimensional singularities in bi dimensional space [7]. Ridgelet transforms is used to extracts low pass energy of character image and is then fed to PCA for feature extraction. We conducted experiment on very large database of handwritten Kannada character. The size of the class was 200 and encouraging results are obtained.
Keywords :
feature extraction; handwritten character recognition; principal component analysis; transforms; Kannada script; PCA; character image; feature extraction; monodimensional singularities; ridgelet transform; unconstrained handwritten Kannada character recognition; Accuracy; Character recognition; Databases; Feature extraction; Handwriting recognition; Principal component analysis; Transforms; Handwritten Character Recognition (HCR); Kannada script; PCA; Ridgelet transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technologies (WICT), 2011 World Congress on
Conference_Location :
Mumbai
Print_ISBN :
978-1-4673-0127-5
Type :
conf
DOI :
10.1109/WICT.2011.6141316
Filename :
6141316
Link To Document :
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