Grey-Level Cooccurrence Matrix Performance Evaluation for Heading Angle Estimation of Moveable Vision System in Static EnvironmentReport as inadecuate




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Journal of SensorsVolume 2013 2013, Article ID 624670, 6 pages

Research Article

Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia

Faculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia

Received 14 March 2013; Accepted 7 May 2013

Academic Editor: Aiguo Song

Copyright © 2013 Zairulazha Zainal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A method of extracting information in estimating heading angle of vision system is presented. Integration of grey-level cooccurrence matrix GLCM in an area of interest selection is carried out to choose a suitable region that is feasible for optical flow generation. The selected area is employed for optical flow generation by using Horn-Schunck method. From the generated optical flow, heading angle is estimated and enhanced via moving median filter MMF. In order to ascertain the effectiveness of GLCM, we compared the result with a different estimation method of optical flow which is generated directly from untouched greyscale images. The performance of GLCM is compared to the true heading, and the error is evaluated through mean absolute deviation MAE. The result ensured that GLCM can improve the estimation result of the heading angle of vision system significantly.





Author: Zairulazha Zainal, Rizauddin Ramli, and Mohd Marzuki Mustafa

Source: https://www.hindawi.com/



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