Change search
ReferencesLink to record
Permanent link

Direct link
Camera calibration by hybrid hopfield network and self-adaptive genetic algorithm
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
Show others and affiliations
2012 (English)In: Measurement Science Review, ISSN 1335-8871, Vol. 12, no 6, 302-308 p.Article in journal (Refereed) Published
Abstract [en]

A new approach based on hybrid Hopfield neural network and self-adaptive genetic algorithm for camera calibration is proposed. First, a Hopfield network based on dynamics is structured according to the normal equation obtained from experiment data. The network has 11 neurons, its weights are elements of the symmetrical matrix of the normal equation and keep invariable, whose input vector is corresponding to the right term of normal equation, and its output signals are corresponding to the fitting coefficients of the camera's projection matrix. At the same time an innovative genetic algorithm is presented to get the global optimization solution, where the cross-over probability and mutation probability are tuned self-adaptively according to the evolution speed factor in longitudinal direction and the aggregation degree factor in lateral direction, respectively. When the system comes to global equilibrium state, the camera's projection matrix is estimated from the output vector of the Hopfield network, so the camera calibration is completed. Finally, the precision analysis is carried out, which demonstrates that, as opposed to the existing methods, such as Faugeras's, the proposed approach has high precision, and provides a new scheme for machine vision system and precision manufacture.

Place, publisher, year, edition, pages
2012. Vol. 12, no 6, 302-308 p.
Keyword [en]
Camera calibration, Hopfield neural network, Longitudinal direction and lateral direction, Projective matrix, Self-adaptive genetic algorithm
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-118421DOI: 10.2478/v10048-012-0042-5ISI: 000314458200011ScopusID: 2-s2.0-84873207276OAI: diva2:606060

QC 20130218

Available from: 2013-02-18 Created: 2013-02-18 Last updated: 2013-03-05Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Zhang, Qing-Ying
By organisation
Production Engineering
In the same journal
Measurement Science Review
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 28 hits
ReferencesLink to record
Permanent link

Direct link