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A novel hidden Markov model (HMM) for recognition of handwritten Oriya numerals is proposed. The novelty lies in the fact that the HMM states are not determined a priori, but are determined automatically based on a database of handwritten numeral images. A handwritten numeral is assumed to be a string of several shape primitives. These are in fact the(More)
We propose support vector machine (SVM) based hierarchical classification schemes for recognition of handwritten Bangla characters. A comparative study is made among multilayer perceptron, radial basis function network and SVM classifier for this 45 class recognition problem. SVM classifier is found to outperform the other classifiers. A fusion scheme using(More)
An efficient method for gene replacement in Lactobacillus helveticus CNRZ32 was developed by utilizing pSA3 as an integration vector. This plasmid is stably maintained in CNRZ32 at 37 degrees C but is unstable at 45 degrees C. This method consisted of a two-step gene-targeting technique: (i) chromosomal integration of a plasmid carrying an internal deletion(More)
Character segmentation is a necessary preprocessing step for character recognition in many handwritten word recognition systems. The most difficult case in character segmentation is the cursive script. Fully cursive nature of Bangla handwriting, the natural skewness in words poses some challenges for automatic character segmentation. In this article a novel(More)
This paper presents a recognition system for isolated handwritten Bangla words, with a fixed lexicon, using a left-right Hidden Markov Model (HMM). A stochastic search method, namely, Genetic Algorithm (GA) is used to train the HMM. A new shape based direction encoding features has been developed and introduced in our recognition system. Both(More)