Handwritten brazilian month recognition: An analysis of two NN architectures and a rejection mechanism

Handwritten brazilian month recognition: An analysis of two NN architectures and a rejection mechanism

Kapp, Marcello N. and Freitas, Cinthia O.De A. and Sabourin, Robert

Proceedings – International Workshop on Frontiers in Handwriting Recognition, IWFHR 2004

Abstract : This paper evaluates the use of the conventional architecture feedforward MLP (multiple layer perception) and class-modular for the handwriting recognition (HWR) and it also compares the results obtained with previous works in terms of recognition rate. This work presents a feature set in full detail to work with HWR. The experiments showed that the class-modular architecture is better than conventional architecture. The obtained average recognition rates were 77.08% using the conventional architecture and 81.75% using the class-modular. This paper also describes a performance study in which a rejection mechanism with multiple thresholds is evaluated for both conventional and class-modular architectures. The multiple thresholds idea is based on the use of N class-related reject thresholds (CRTs). The results indicate that this rejection mechanism can be used appropriately in both architectures. The experimental results are 86.38% and 91.52% using a handwritten months word database © 2004 IEEE.