DocumentCode
3059896
Title
Statistical and neural classification of handwritten numerals: a comparative study
Author
Cao, Jun ; Shridhar, M. ; Kimura, F. ; Ahmadi, M.
Author_Institution
Michigan-Dearborn Univ., MI, USA
fYear
1992
fDate
30 Aug-3 Sep 1992
Firstpage
643
Lastpage
646
Abstract
Presents the results obtained in a performance evaluation study on the recognition of handwritten numerals, using a statistical classifier and a neural network. The features consist of direction sensitive spatial features derived from the digitized image of the numeral. Studies with a large numeral database indicate that the overall performance of the neural net is better than that of the statistical classifier
Keywords
character recognition; feature extraction; neural nets; digitized image; direction sensitive spatial features; handwritten numerals; neural classification; neural network; performance evaluation; statistical classifier; Covariance matrix; Data mining; Data processing; Estimation error; Feature extraction; Handwriting recognition; Histograms; Hydrogen; Image databases; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
Conference_Location
The Hague
Print_ISBN
0-8186-2915-0
Type
conf
DOI
10.1109/ICPR.1992.201859
Filename
201859
Link To Document