Seal object detection in document images using GHT of local component shapes
Proceedings of the 2010 ACM Symposium on Applied Computing
Query driven word retrieval in graphical documents
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Touching text character localization in graphical documents using SIFT
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
Document seal detection using GHT and character proximity graphs
Pattern Recognition
Zoning methods for handwritten character recognition: A survey
Pattern Recognition
Hi-index | 0.00 |
In this paper, we present a scheme towards the segmentation of English multi-oriented touching strings into individual characters. When two or more characters touch, they generate a big cavity region at the background portion. Using Convex Hull information, we use these background information to find some initial points to segment a touching string into possible primitive segments (a primitive segment consists of a single character or a part of a character). Next these primitive segments are merged to get optimum segmentation and dynamic programming is applied using total likelihood of characters as the objective function. SVM classifier is used to find the likelihood of a character. To consider multi-oriented touching strings the features used in the SVM are invariant to character orientation. Circular ring and convex hull ring based approach has been used along with angular information of the contour pixels of the character to make the feature rotation invariant. From the experiment, we obtained encouraging results.