Keyword spotting on Hangul document images using two-level image-to-image matching

Authors:
Sang Cheol Park;Hwa Jeong Son;Chang Bu Jeong;Soo Hyung Kim
Affiliations:
Department of Computer Science, Chonnam National University, Yongbong-dong, Buk-gu, Kwangju, Korea;Department of Computer Science, Chonnam National University, Yongbong-dong, Buk-gu, Kwangju, Korea;Department of Computer Science, Chonnam National University, Yongbong-dong, Buk-gu, Kwangju, Korea;Department of Computer Science, Chonnam National University, Yongbong-dong, Buk-gu, Kwangju, Korea
Venue:
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Year:
2005

Citing 2
Cited 0

The indexing and retrieval of document images: a survey

Computer Vision and Image Understanding - Special issue on document image understanding and retrieval
A Keyword Spotting System of Korean Document Images

ICADL '02 Proceedings of the 5th International Conference on Asian Digital Libraries: Digital Libraries: People, Knowledge, and Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

A lot of printed documents and books has been published and saved as a form of images in digital libraries. Searching for a specified query word on document images is a challenging problem. The OCR software helps the images to be converted to the machine readable documents to search a full context [1]. Another approach [1, 2] is image-based one, in which both the document images and word information are saved in a database. The searching procedure is accomplished through comparing the features of query word image with the word images extracted from document images in the database. In this paper, we propose an accurate and fast keyword spotting system for searching user-specified keyword in Hangul document images by a two-level image-to-image matching method.