Title :
An improved two-layer SOM classifier for handwritten numeral recognition
Author :
Lu, Shujing ; Tu, Xiao ; Lu, Yue
Author_Institution :
Shanghai Res. Inst. of China Post Group, Shanghai
Abstract :
In the past several years, wepsilave been developing a high performance two-layer SOM classifier for handwritten Bangla numeral recognition. We have reported previously the structure and the learning algorithm of the two-layer SOM. In this paper, we fuse the outputs of the second layer SOMs to improve the classification ability, based on confidence coefficient of the SOMs in the second layer. Experimental results on the numeral images obtained from real Bangladesh envelopes have proved the validity of the proposed method.
Keywords :
handwritten character recognition; image classification; image fusion; learning (artificial intelligence); natural languages; self-organising feature maps; confidence coefficient; handwritten Bangla numeral recognition; image fusion; learning algorithm; two-layer SOM classifier; Computer science; Error analysis; Fuses; Handwriting recognition; Merging; Neurons; Pattern recognition; Unsupervised learning; Vector quantization; Voting;
Conference_Titel :
Computer and Information Technology, 2008. CIT 2008. 8th IEEE International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4244-2357-6
Electronic_ISBN :
978-1-4244-2358-3
DOI :
10.1109/CIT.2008.4594703