System Maintenance:
There may be intermittent impact on performance while updates are in progress. We apologize for the inconvenience.
By Topic

Robust multi-dimensional Null Space representation for image retrieval and classification

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)
Xu Chen ; Dept. of Electr. & Comput. Eng., Univ. of Illinois at Chicago, Chicago, IL ; Schonfeld, D. ; Khokhar, A.

This paper presents a novel system for image retrieval and classification based on a robust multi-dimensional view invariant representation and a linear classifier algorithm. Specifically, multi-dimensional null space invariant (NSI) matrix representation has been derived. Moreover, the robustness of null space representation has been investigated with perturbation analysis in terms of the error ratio and SNR. The proposed representation is invariant to affine transformations and preserves the null space matrix. We use principal component null space analysis (PCNSA) of the NSI operator for recognition, indexing, and retrieval of 2D and 3D images. We rely on PCNSA to determine the distance of a query image to the centroid of the class, which is a statistical information vector in the PCNSA algorithm representing the corresponding class of the object. Our results shows that NSI provides a robust and powerful approach to image recognition and classification even when the query image or the stored image has been subjected to unknown affine transformations due to camera motions.

Published in:

Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on

Date of Conference:

12-15 Oct. 2008