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Author Ashoka H., N. ♦ Manjaiah D., H. ♦ Bera, Rabindranath
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Feature Extraction ♦ Kannada Handwritten Numeral Recognition ♦ Statistical Classification Technique ♦ Kannada Handwritten Numeral Database ♦ Different Individual ♦ Binary Image ♦ Real Value ♦ Statistical Classifier Build ♦ Particular Window Size ♦ Recognition Rate
Abstract Abstract—This paper presents the zone based feature extraction and statistical classification technique for Kannada handwritten numeral recognition. The Kannada handwritten numeral database required for the experimentation is collected from the different individuals and are preprocessed for feature extraction. The binary images fitted in a particular window size are partitioned into a number of regions and a real value is computed by the density of one’s to represent the image. The statistical classifier build for the experimentation and on Kannada handwritten numeral database found better classification and recognition rate.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study