Abstract
We consider the problem of designing a vision system for tracking parcels moving on a conveyor belt. After computing parcels dimensions, i.e., length, width and height, at the entrance of the conveyor belt using a stereo camera pair, the vision system incorporates 30fps grayscale image input from 4 cameras equally spaced over the conveyor belt, and computes in real-time the location of each parcel over the belt. The corner points of the tracked parcels are then sent to a controller, which arranges the parcels into a single line at the output. We use Lucas-Kanade-Tomasi (LKT) feature tracking algorithm as the base of our tracking algorithm: Corner points of a parcel from the previous frame are fed into the LKT algorithm to get the new corner coordinates of the parcel in the current frame. Although this approach tracks a parcel for a few frames over the belt, it is not enough for long-term successful tracking of a parcel. To achieve successful parcel tracking, an edge mapping is added as a refinement step following LKT corner tracking. In this paper we detail the design and implementation of our tracking software and show that the proposed algorithms are novel and are able to track parcels in real-time.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Eltoukhy, H., Salama, K.: Multiple Camera Tracking, Project Report (2002)
Stefano, L.D., Viarani, E.: Vehicle Detection and Tracking Using the Blocking Algorithm. In: Proc. of 3rd IMACS/IEEE Int’l Multiconference on Circuits, Systems, Communications and Computer, Athens, Greece, vol. 1, pp. 4491–4496 (1999)
Shi, J., Tomasi, C.: Good Features to Track. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 593–600 (1994)
Wong, K.Y., Spetsakis, M.E.: Tracking, Segmentation and Optical Flow. In: Proceedings of 16th International Conference on Vision Interface, S1.5, Halifax, Canada, pp. 57–64 (2003)
Lucas, B.D., Kanade, T.: An Iterative Image Registration Technique with an Application to Stereo Vision. In: International Joint Conference on Artificial Intelligence, pp. 674–679 (1981)
Liu, H., Hong, T.H., Herman, M., Chellappa, R.: Accuracy vs. Efficiency Trade offs in Optical Flow Algorithms. Computer Vision and Image Understanding 72, 271–286 (1998)
Barron, J.L., Fleet, D.J., Beauchemin, S.S.: Performance of Optical Flow Techniques. Int J Comp Vis 12(1), 43–77 (1994)
Tomasi, C., Kanade, T.: Detection and Tracking of Point Features, Carnegie Mellon University Technical Report CMU-CS-91-132 (1991)
Bresenham, J.E.: Algorithm for Computer Control of a Digital Plotter. IBM Systems Journal 4(1), 25–30 (1965)
Bresenham, J.E.: A linear Algorithm for Incremental Digital Display of Circular Arcs. Communications of the ACM 20(2), 100–106 (1977)
Baker, S., Gross, R., Matthews, I.: Lucas-Kanade 20 years on: A unifying frame work Part 4, Technical Report CMU-RI-TR-04-14, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA (2004)
Pitteway, M.L.V.: Algorithm for Drawing Ellipses or Hyperbolae with a Digital lotter. Computer J. 10(3), 282–289 (1967)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Karaca, H.N., Akınlar, C. (2005). A Multi-camera Vision System for Real-Time Tracking of Parcels Moving on a Conveyor Belt. In: Yolum, p., Güngör, T., Gürgen, F., Özturan, C. (eds) Computer and Information Sciences - ISCIS 2005. ISCIS 2005. Lecture Notes in Computer Science, vol 3733. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11569596_73
Download citation
DOI: https://doi.org/10.1007/11569596_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29414-6
Online ISBN: 978-3-540-32085-2
eBook Packages: Computer ScienceComputer Science (R0)