Adaptive Hindi OCR Using Generalized Hausdorff Image Comparison
Adaptive Hindi OCR Using Generalized Hausdorff Image Comparison
Loading...
Files
Publication or External Link
Date
2003-09-25
Authors
Ma, Huanfeng
Doermann, David
Advisor
Citation
DRUM DOI
Abstract
In this paper, we present an adaptive Hindi OCR using generalized Hausdor
image comparison implemented as part of a rapidly retargetable language tool
reort. The system includes: script identification, character segmentation,
training sample creation and character recognition. The OCR design
(completed in one month) was applied to a complete Hindi-English bilingual
dictionary (with 1083 pages) and a collection of ideal images extracted from
Hindi documents in PDF format. Experimental results show the recognition
accuracy can reach 88% for noisy images and 95% for ideal images, both at
the character level. The presented method can also be extended to design OCR
systems for different
scripts.
(LAMP-TR-105)
(CAR-TR-987)
(UMIACS-TR-2003-87)