A search engine for imaged documents in PDF files
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Feature string-based intelligent information retrieval from Tamil document images
International Journal of Computer Applications in Technology
A survey of keyword spotting techniques for printed document images
Artificial Intelligence Review
Word extraction from table regions in document images
ICADL'05 Proceedings of the 8th international conference on Asian Digital Libraries: implementing strategies and sharing experiences
| Hi-index | 0.00 |
A great number of documents are scanned and archived in the form of digital images in digital libraries, to make them available and accessible in the Internet. Information retrieval in these imaged documents has become a growing and challenging problem. For this purpose, a word image coding technique is proposed in this paper, and a web-based system for efficiently retrieving imaged documents from digital libraries is described. Some image preprocessingis first carried out off-line to extract word objects from imaged documents stored in the digital library. Then each word object is represented by a string of feature codes. As a result, each document image is represented by a series of feature code strings of its words, which are stored in a feature code file. Upon receiving a user's request, the server converts the query word into feature code string using the same conversion mechanism as is used in producing feature codes for the underlying imaged documents. Searching is then performed among those feature code .les generated of.ine. An inexact string matching technique, with the ability of matching a word portion, is applied to match the query word with the words in the documents, and then the occurrence frequency of the query word in each corresponding document is calculated for relevant ranking. Preliminary experimental results with some imaged documents of students' theses in the digital library of our university show that the proposed approach is efficient and promising for retrieving imaged documents, with potential applications to digital libraries.