Cart (Loading....) | Create Account
Close category search window

Gabor filter based block energy analysis for text extraction from digital document images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Sabari Raju, S. ; Dept. of Electr. Eng., Indian Inst. of Sci., Bangalore, India ; Peeta Basa Pati ; Ramakrishnan, A.G.

Extraction of text areas is a necessary first step for taking a complex document image for diameter recognition task. In digital libraries, such OCR'ed text facilitates access to the image of document page through keyword search. Gabor filters, known to be simulating certain characteristics of the human visual system (HVS), have been employed for this task by a large number of scientists, in scanned document images. Adapting such a scheme for camera based document images is a relatively new approach. Moreover, design of the appropriate filters to separate text areas, which are assumed to be rich in high frequency components, from nontext areas is a difficult task. The difficulty increases if the clutter is also rich in high frequency components. Other reported works, on separating text from nontext areas, have used geometrical/structural information like shape and size of the regions in binarized document images. In this work, we have used a combination of the above mentioned approaches for the purpose. We have used connected component analysis (CCA), in binarized images, to segment nontext areas based on the size information of the connected regions. A Gabor function based filter bank is used to separate the text and the nontext areas of comparable size. The technique is shown to work efficiently on different kinds of scanned document images, camera captured document images and sometimes on scenic images.

Published in:

Document Image Analysis for Libraries, 2004. Proceedings. First International Workshop on

Date of Conference:


Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.