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

A Geometry-Distortion Resistant Image Detection System Based on Log-Polar Transform and Scale Invariant Feature Transform

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

4 Author(s)
Shang-Lin Hsieh ; Dept. of Comput. Sci. & Eng., Tatung Univ., Taipei, Taiwan ; Yu-Wei Chen ; Chun-Che Chen ; Tsun-Wei Chang

This paper presents an image detection system based on Log-Polar Transform (LPT) and Scale Invariant Feature Transform (SIFT). Unlike other schemes that extract features from the original image, the presented scheme extracts features from the transformed image by LPT. Moreover, the presented scheme utilizes SIFT to extract geometric-invariant features from the LPT images to achieve greater robustness and resistance to geometric distortion. When given a suspect image, the scheme compares the extracted features from the host LPT image and the suspect LPT image to determine similarity. The experimental results show the presented scheme can achieve high recall and precision rates even when the duplicate image is modified and not exactly the same as the host one.

Published in:

High Performance Computing and Communications (HPCC), 2011 IEEE 13th International Conference on

Date of Conference:

2-4 Sept. 2011

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.