Fourier fuzzy neural network for clustering of objects based on the gross shape and its application to handwritten character recognition

Author

Patil, Pradeep M. ; Deshmukh, Manish P.

Author_Institution

Vishwakarma Inst. of Technol., India

Volume

3

fYear

2005

fDate

31 July-4 Aug. 2005

Firstpage

1918

Abstract

In this paper an unsupervised feed forward Fourier fuzzy neural network (FFNN) is proposed which is suitable for clustering of object images based on their gross shapes. This 3-layer feed forward neural network is described along with its training. Its performance is tested for synthetic image database containing objects of various shapes and with realistic image database of handwritten Devanagari digits. Performance of FFNN is found superior than the fuzzy min-max neural network (FMN) clustering by P.M. Patil et al. (2002), and it takes less recall time per pattern than FMN.

Keywords

feedforward neural nets; fuzzy neural nets; handwritten character recognition; pattern clustering; unsupervised learning; gross shape; handwritten Devanagari digit; handwritten character recognition; object image clustering; realistic image database; synthetic image database; unsupervised feed forward Fourier fuzzy neural network; Character recognition; Feature extraction; Feeds; Fuzzy neural networks; Image databases; Image recognition; Network topology; Neural networks; Pattern recognition; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on

Print_ISBN

0-7803-9048-2

Type

conf

DOI

10.1109/IJCNN.2005.1556173

Filename

1556173