Soft primitive extraction on handwritten digits

Author

Boujemaa, N. ; Roux, G. ; De Beauville, J. P Asselin ; Vattolo, B.

Author_Institution

Lab. d´´Inf., Ecole d´´Ingenieurs en Inf. pour l´´Ind., Tours, France

Volume

3

fYear

1997

Firstpage

296

Abstract

Recognition of handwritten digits is useful for several applications such as automatic bank cheques interpretation. Many problems occur, making this task quite difficult: digits may overlap, the removal of a base line may damage the digits, and noise quantization pixels may alter the digits shape and meaning, etc. Uncertainty modeling becomes essential to our work. This paper shows how robust fuzzy clustering techniques are suitable and useful for soft feature extraction and representation of a cheque´s numerical value

Keywords

bank data processing; curve fitting; feature extraction; fuzzy systems; handwriting recognition; image representation; image segmentation; automatic bank cheques interpretation; curve fitting; digits meaning; digits shape; handwritten digits recognition; noise quantization pixels; numerical value; robust fuzzy clustering techniques; segmentation; soft feature extraction; soft feature representation; soft primitive extraction; uncertainty modeling; Automatic frequency control; Change detection algorithms; Clustering algorithms; Equations; Euclidean distance; Feature extraction; Multi-stage noise shaping; Noise robustness; Prototypes; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1997. Proceedings., International Conference on

Conference_Location

Santa Barbara, CA

Print_ISBN

0-8186-8183-7

Type

conf

DOI

10.1109/ICIP.1997.632096

Filename

632096