This paper describes a complete system for the recognition of isolated handwritten Devnagri character using Fourier Descriptor and Hidden-Markov model (HMM). The HMM has the property that its states are not defined as a priory information, but are determined automatically based on a database of handwritten numerals images. In this work the image database consist of 500 images of handwritten Dev...

This paper introduces a novel feature extraction approach for handwritten Assamese character recognition. The performance of an optical character recognition system highly depends on the extracted feature set. Hence, feature extraction plays a significant role in achieving high recognition accuracy. Also, not all the features of an image are useful for classification and therefore feature extra...

This paper deals with the recognition of off-line handwritten Devnagari characters. Here two sets of feature are computed and two classifiers are combined to get higher accuracy of Devnagari character recognition. Dimension of the features vector of each set is 392. First feature set is computed based on the directional information obtained from the arc tangent of the gradient. Since most of th...

In this paper, we present a study on sample preselection in large training data set for CNN-based classification. To do so, we structure the input data set in a network representation, namely the Relative Neighbourhood Graph, and then extract some vectors of interest. The proposed preselection method is evaluated in the context of handwritten character recognition, by using two data sets, up to...

Optical Character Recognition (OCR) is a process to recognize the handwritten or printed scanned text with the help of a computer. Segmentation is very important stage of any text recognition system. The problems in segmentation can lead to decrease in segmentation rate and hence recognition rate. A good segmentation technique can improve the recognition rate. This paper deals with the hazards ...

We propose a trajectory planning and control theory for continuous movements such as connected cursive handwriting and continuous natural speech. Its hardware is based on our previously proposed forward-inverse-relaxation neural network (Wada & Kawato, 1993). Computationally, its optimization principle is the minimum torquechange criterion. Regarding the representation level, hard constraints s...

Experiments involving handwritten word recognition on words taken from images of handwritten address blocks from the United States Postal Service mailstream are described. The word recognition algorithm relies on the use of neural networks at the character level. The neural networks were trained using crisp and fuzzy desired outputs. The fuzzy outputs were defined using a fuzzy k-nearest neighb...

Video-based handwritten Character Recognition (VCR) system is a new type of character recognition system with many unique advantages over on-line character recognition system. Its main problem is to effectively extract stroke dynamic information from video data for character recognition. In this paper, we propose a new stroke extraction algorithm through dynamic stroke information analysis for ...