Name
Abstract | ||
|---|---|---|
Edit distance matching has been used in literature for word spotting with characters taken as primitives. The recognition rate however, is limited by the segmentation inconsistencies of characters (broken or merged) caused by noisy images or distorted characters. In this paper, we have proposed a Merge-split edit distance which overcomes these segmentation problems by incorporating a multi-purpose merge cost function. The system is based on the extraction of words and characters in the text and then attributing each character with a set of features. Characters are matched by comparing their extracted feature sets using Dynamic Time Warping (DTW) while the words are matched by comparing the strings of characters using the proposed Merge-Split Edit distance algorithm. Evaluation of the method on 19th century historical document images exhibits extremely promising results. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-03767-2_26 | CAIP |
Keywords | Field | DocType |
merge-split edit distance,dynamic time warping.,distorted character,proposed merge-split edit distance,distance matching,promising result,noisy image,dynamic time warping,century historical document image,novel approach,word spotting,segmentation inconsistency,cost function,segmentation problem,edit distance | Edit distance,Pattern recognition,Dynamic time warping,Segmentation,Computer science,Wagner–Fischer algorithm,Speech recognition,Artificial intelligence,Merge (version control),Spotting,Historical document | Conference |
Volume | ISSN | Citations |
5702 | 0302-9743 | 6 |
PageRank | References | Authors |
0.47 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Khurram Khurshid | 1 | 129 | 15.94 |
| Claudie Faure | 2 | 133 | 10.62 |
| Nicole Vincent | 3 | 195 | 12.09 |