95 citations · 181 across the 7 of their papers we have counts for
7 papers
Classification Of Gradient Change Features Using MLP For Handwritten Character Recognition
Sandhya Arora, Latesh Malik, Debotosh Bhattacharjee +1
A novel, generic scheme for off-line handwritten English alphabets character images is proposed. The advantage of the technique is that it can be applied in a generic manner to dif…
A novel approach for handwritten Devnagari character recognition
Sandhya Arora, Latesh Malik, Debotosh Bhattacharjee +1
In this paper a method for recognition of handwritten devanagari characters is described. Here, feature vector is constituted by accumulated directional gradient changes in differe…
A Two Stage Classification Approach for Handwritten Devanagari Characters
Sandhya Arora, Debotosh Bhattacharjee, Mita Nasipuri +1
The paper presents a two stage classification approach for handwritten devanagari characters The first stage is using structural properties like shirorekha, spine in character and…
Multiple Classifier Combination for Off-line Handwritten Devnagari Character Recognition
Sandhya Arora, Debotosh Bhattacharjee, Mita Nasipuri +2
This work presents the application of weighted majority voting technique for combination of classification decision obtained from three Multi_Layer Perceptron(MLP) based classifier…
Application of Statistical Features in Handwritten Devnagari Character Recognition
S. Arora, Debotosh Bhattacharjee, M. Nasipuri +2
In this paper a scheme for offline Handwritten Devnagari Character Recognition is proposed, which uses different feature extraction methodologies and recognition algorithms. The pr…
Recognition of Non-Compound Handwritten Devnagari Characters using a Combination of MLP and Minimum Edit Distance
Sandhya Arora, Debotosh Bhattacharjee, Mita Nasipuri +2
This paper deals with a new method for recognition of offline Handwritten non-compound Devnagari Characters in two stages. It uses two well known and established pattern recognitio…