doi: 10.7763/IJIET.2012.V2.88
Combining Kalman Filter with Mixture Color Model Tracking of Pallet Image
Ssu-Wei Chen1
,
Luke K. Wang1 ,
Jen-Hong Lan1 ,
Jia-Lin Tu2
- 1Department of Electrical Engineering of National Kaohsiung University of Applied Sciences, Kaohsiung, 80778 Taiwan, R.O.C
- 2Department of Biomedical Informatics of Asia University, Taichung, 41354 Taiwan, R.O.C
Abstract
In this paper, we propose combining the mixture color model with Kalman filter method. The purpose is to enable forklifts to search for pallets, but it is able to meet fully automated system with real-time. We focused on pallets for image feature and tracking. First, we manually segmented 30 pallet images and statistics of the best color threshold, this method must find the threshold of different color space and mixture of two important color spaces containing HSV and YCbCr, we extracted the H and the Cb composition mixtures to find the best color threshold, and using a combination of Kalman filter(KF) and the color model method to track pallet images, we then used the logic function to keep our information after obtaining the color image segmentation, the noise of the image must be removed, this algorithm can be used on video sequences efficiently. Finally, experimental results show that the method has effective tracking pallet images in the video sequences.
Keywords
- Kalman filter
- color space
- object tracking
- image detection
How to Cite
Ssu-Wei Chen, Luke K. Wang, Jen-Hong Lan, and Jia-Lin Tu, "Combining Kalman Filter with Mixture Color Model Tracking of Pallet Image," International Journal of Information and Education Technology, vol. 2, no. 2, pp. 88-93, 2012. https://doi.org/10.7763/IJIET.2012.V2.88
Copyright & License
Copyright © 2012 by the authors. 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 (CC BY 4.0).