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Pattern recognition in grey level images using moment based invariant features

Paschalakis, Stavros and Lee, Peter (1999) Pattern recognition in grey level images using moment based invariant features. In: Seventh International Conference on Image Processing And Its Applications, 1999. Conference Publications . IEEE, pp. 245-249. ISBN 0-85296-717-9. (doi:10.1049/cp:19990320) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1049/cp:19990320

Abstract

Moment based invariants, in various forms, have been widely used over the years as features for recognition in many areas of image analysis. Typical examples include the use of moments for optical character recognition and shape identification. However, most of the work that has been carried out to date using moments and moment invariants is concerned with the identification of distinct shapes using binary images. There can be cases, though, where the different objects to be recognised share identical shapes and binary images fail to convey the necessary information to the recognition processes. The work presented in this paper not only looks at object recognition using binary images, but also addresses the issue of classification among objects which have identical shapes, using grey level images for the moment calculations. Two different moment based feature vectors that provide translation, scale, contrast and rotation invariance are used for the recognition of the different objects. These are the complex moments magnitudes and the Hu (1962) moment invariants. The performance of these two feature vectors are assessed both in the presence and absence of noise and the effect of extending the order of the moments used in their calculations is investigated.

Item Type: Book section
DOI/Identification number: 10.1049/cp:19990320
Additional information: Proceedings Paper; Issue: 465;
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications)
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Depositing User: F.D. Zabet
Date Deposited: 01 May 2009 16:31 UTC
Last Modified: 26 Jul 2019 13:52 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/16441 (The current URI for this page, for reference purposes)
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