2 research outputs found
Time Efficient Approach To Offline Hand Written Character Recognition Using Associative Memory Net
In this paper, an efficient Offline Hand Written Character Recognition
algorithm is proposed based on Associative Memory Net (AMN). The AMN used in
this work is basically auto associative. The implementation is carried out
completely in 'C' language. To make the system perform to its best with minimal
computation time, a Parallel algorithm is also developed using an API package
OpenMP. Characters are mainly English alphabets (Small (26), Capital (26))
collected from system (52) and from different persons (52). The characters
collected from system are used to train the AMN and characters collected from
different persons are used for testing the recognition ability of the net. The
detailed analysis showed that the network recognizes the hand written
characters with recognition rate of 72.20% in average case. However, in best
case, it recognizes the collected hand written characters with 88.5%. The
developed network consumes 3.57 sec (average) in Serial implementation and 1.16
sec (average) in Parallel implementation using OpenMP
Non-Correlated Character Recognition using Artificial Neural Network
This paper investigates a method of Handwritten English Character Recognition
using Artificial Neural Network (ANN). This work has been done in offline
Environment for non correlated characters, which do not possess any linear
relationships among them. We test that whether the particular tested character
belongs to a cluster or not. The implementation is carried out in Matlab
environment and successfully tested. Fifty-two sets of English alphabets are
used to train the ANN and test the network. The algorithms are tested with 26
capital letters and 26 small letters. The testing result showed that the
proposed ANN based algorithm showed a maximum recognition rate of 85%.Comment: appeared in: proceedings of National Conference on Dynamics and
Prospects of Data Mining: Theory and Practices (DPDM)-2012; September 30,
2012, India; Publisher: OITS-BLS, Balasore Chapter; Proceeding ISBN:
987-93-81361-31-6, pp. 79-8