In this digital world, everything including documents, notes is kept in form. The requirement of converting these documents into processed information demand. This process called as Handwritten digit recognition (HDR). scan document and classified to identify the hand written words text so that it can be used keep format means computerized font everybody read properly. paper, discussed classifi...

This paper addresses the automatic recognition of handwritten temperature values in weather records. The localization of table cells is based on line detection using projection profiles. Further, a stroke-preserving line removal method which is based on gradient images is proposed. The presented digit recognition utilizes features which are extracted using a set of filters and a Support Vector ...

This paper introduces a hierarchical Gabor features(HGFs) and hierarchical bayesian network(HBN) for handwritten digit recognition. The HGFs represent a different level of information which is structured such that the higher the level, the more global information they represent, and the lower the level, the more localized information they represent. The HGFs are extracted by the Gabor filters s...

This paper presents a hidden Markov model (HMM) based approach to on-line handwritten digit recognition using stroke sequences. In this approach, a character instance is represented by a sequence of symbolic strokes, and the representation is obtained by component segmentation and stroke classification. The component segmentation is based on the delta lognormal model of handwriting generation. ...

We present the results of several unsupervised algorithms tested on the MNIST database as well as techniques we used to improve the classification accuracy. We find that spiking neural network outperforms kmeans clustering and reaches the same level as the supervised SVM. We then discuss several inherent issues of unsupervised methods for the handwritten digit classfication problem and propose ...

Image processing is a technique that can identify shades, colors and relationships that cannot be perceived by the human eye. It is used to solve identification problems such as in forensic medicine or in creating weather maps from satellite pictures. It deals with images in bitmapped graphics format that has been scanned or captured with digital cameras. Image processing is a form of signal pr...

Neural network ensembles are applied to handwritten digit recognition. The invidual networks of the ensemble are combinations of sparse Look-Up Tables with random receptive fields. It is shown that the consensus of a group of networks outperform the best invidual of the ensemble and further we show that it is possible to estimate the ensemble performance as well as the learning curve, on a medi...

In this paper, new features called Slope Detail (SD) features for handwritten digit recognition have been introduced. These features are based on shape analysis of the digit image and extract slant or slope information. They are effective in obtaining good recognition accuracies. When combined with commonly used features, Slope Detail features enhance the digit recognition accuracy. KNearest Ne...

Handwritten Numeral recognition plays a vital role in postal automation services especially in countries like India where multiple languages and scripts are used Discrete Hidden Markov Model (HMM) and hybrid of Neural Network (NN) and HMM are popular methods in handwritten word recognition system. The hybrid system gives better recognition result due to better discrimination capability of the N...