Applications

Flusser, DSc Jan; Head, Barbara Zitová PhD

doi:10.1002/9780470684757.ch8

Moments and Moment Invariants in Pattern Recognition 2009

DOI: 10.1002/9780470684757.ch8

|View full text |Cite

Applications

DSc Jan Flusser

Barbara Zitová PhD Head

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2022

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 98 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A Blend of Analytical and Numerical Methods to Compute Orthogonal Image Moments over a Unit Disk

Singh

Kumar

Bhatnagar

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Accurate image moment computation is critical because they are used in a variety of fields, including image reconstruction and object recognition. Orthogonal polynomials are frequently used to compute moments due to their numerous intersecting and important theoretical properties. In polar coordinate systems, orthogonal polynomials such as the Polar Harmonic Fourier Transform (PHFT) and Polar Harmonic Transformation (PHT) are defined. However, the images are defined by a Cartesian coordinate system. To obtain image moments, a double integration over a unit circle over the product of the PHFT or PHT and the image function must be performed. The choice of double integration techniques and domain for the double integral has a significant effect on the precision of the computed moments. We have proposed a method for using the entire unit circle as an integration domain in this study, for image reconstruction. We used the PHFT and PHT to apply this technique to computing moments for the reconstruction. The proposed method outperforms other state-of-the-art methods, including Gaussian quadrature numerical integration method (GQM) and zeroth order approximation (ZOA) on variety of scenarios using three benchmarked image sets. We have demonstrated experimentally that this technique significantly improves the accuracy of image moments in higher order moments, as measured by reduced mean squared error (MSE). Additionally, the proposed method significantly improved the moment’s rotational (an improvement of 1-3% as compared to GQM and an improvement of 37-93% as compared to ZOA) and scaling invariance (an improvement of 0-500% as compared to GQM and an improvement of 3-7000% as compared to ZOA).

show abstract

A Blend of Analytical and Numerical Methods to Compute Orthogonal Image Moments over a Unit Disk

Singh

Kumar

Bhatnagar

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Applications

Cited by 1 publication

References 98 publications

A Blend of Analytical and Numerical Methods to Compute Orthogonal Image Moments over a Unit Disk

A Blend of Analytical and Numerical Methods to Compute Orthogonal Image Moments over a Unit Disk

Contact Info

Product

Resources

About