Name
Abstract | ||
|---|---|---|
This paper presents an implementation to recognin Online Handwritten Gurmuldri strokes using Support Vector Machine. This implementation starts with a phase named Preprocessing, which consists of 5 basic algorithms. Prior to these algorithms, a basic step called Stroke Capturing is done, which samples data points along the trajectory of an input device. After preprocessing, recognition of Gurmuldri stroke is done using Support Vector Machine with the help of two cross validation techniques, namely, holdout and k-fold. The recognition is based on the unique IDs identified as the strokes in order to represent a Punjabi akshar (word). These strokes are taken from the one hundred Punjabi words written by 3 different writers. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-81-322-1038-2_42 | PROCEEDINGS OF SEVENTH INTERNATIONAL CONFERENCE ON BIO-INSPIRED COMPUTING: THEORIES AND APPLICATIONS (BIC-TA 2012), VOL 1 |
Keywords | Field | DocType |
Online Handwriting Recognition,Gurmukhi Strokes,Preprocessing,Feature Computation,Support Vector Machines | Data point,Pattern recognition,Computer science,Support vector machine,Preprocessor,Artificial intelligence,Computer Applications,Hidden Markov model,Cross-validation,Trajectory,Input device | Conference |
Volume | ISSN | Citations |
201 | 2194-5357 | 1 |
PageRank | References | Authors |
0.35 | 16 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mayank Gupta | 1 | 118 | 10.60 |
| Nainsi Gupta | 2 | 1 | 0.35 |
| Rakesh Agrawal | 3 | 29751 | 5959.33 |