Object Motion Tracking Based On Color Detection for Android Devices
This paper presents the development of a robot car
that can track the motion of an object by detecting its color through
an Android device. The employed computer vision algorithm uses the
OpenCV library, which is embedded into an Android application of a
smartphone, for manipulating the captured image of the object. The
captured image of the object is subjected to color conversion and is
transformed to a binary image for further processing after color
filtering. The desired object is clearly determined after removing
pixel noise by applying image morphology operations and contour
definition. Finally, the area and the center of the object are
determined so that object’s motion to be tracked. The smartphone
application has been placed on a robot car and transmits by Bluetooth
to an Arduino assembly the motion directives so that to follow
objects of a specified color. The experimental evaluation of the
proposed algorithm shows reliable color detection and smooth
tracking characteristics.
[1] Tang Sze Ling et al, “Colour-based Object Tracking in Surveillance
Application”, Proceedings of the International MultiConference of
Engineers and Computer Scientists, vol. I, Hong Kong, March 2009.
[2] J.F. Engelberger, “Health-care Robotics Goes Commercial: The
Helpmate Experience”, Robotics, vol. 11, 1993, pp. 517-523.
[3] L. Davis, V. Philomin and R. Duraiswami, “Tracking Humans from a
Moving Platform”, IEEE Computer Society Proceedings of the
International Conference on Pattern Recognition, vol. 4, 2000, pp. 4171.
[4] O. Javed and M.S. Yilmaz, “Object Tracking: A survey”, ACM Journal
of Computing Surveys, vol. 38, no. 4, article 13, 2006.
[5] D. Comanciu, P. Meer, “Mean shift: A robust approach toward feature
space analysis”, IEEE Transactions on Pattern Analysis Machine
Intelligence, vol. 24, no. 5, 2002, pp. 603–619.
[6] D. Comanciu, V. Ramesh, P. Meer, “Kernel-based object tracking”,
IEEE Transactions on Pattern Analysis Machine Intelligence, vol. 25,
2003, pp. 564–575.
[7] http://opencv.org/platforms/android.html
[1] Tang Sze Ling et al, “Colour-based Object Tracking in Surveillance
Application”, Proceedings of the International MultiConference of
Engineers and Computer Scientists, vol. I, Hong Kong, March 2009.
[2] J.F. Engelberger, “Health-care Robotics Goes Commercial: The
Helpmate Experience”, Robotics, vol. 11, 1993, pp. 517-523.
[3] L. Davis, V. Philomin and R. Duraiswami, “Tracking Humans from a
Moving Platform”, IEEE Computer Society Proceedings of the
International Conference on Pattern Recognition, vol. 4, 2000, pp. 4171.
[4] O. Javed and M.S. Yilmaz, “Object Tracking: A survey”, ACM Journal
of Computing Surveys, vol. 38, no. 4, article 13, 2006.
[5] D. Comanciu, P. Meer, “Mean shift: A robust approach toward feature
space analysis”, IEEE Transactions on Pattern Analysis Machine
Intelligence, vol. 24, no. 5, 2002, pp. 603–619.
[6] D. Comanciu, V. Ramesh, P. Meer, “Kernel-based object tracking”,
IEEE Transactions on Pattern Analysis Machine Intelligence, vol. 25,
2003, pp. 564–575.
[7] http://opencv.org/platforms/android.html
@article{"International Journal of Information, Control and Computer Sciences:69967", author = "Zacharenia I. Garofalaki and John T. Amorginos and John N. Ellinas", title = "Object Motion Tracking Based On Color Detection for Android Devices", abstract = "This paper presents the development of a robot car
that can track the motion of an object by detecting its color through
an Android device. The employed computer vision algorithm uses the
OpenCV library, which is embedded into an Android application of a
smartphone, for manipulating the captured image of the object. The
captured image of the object is subjected to color conversion and is
transformed to a binary image for further processing after color
filtering. The desired object is clearly determined after removing
pixel noise by applying image morphology operations and contour
definition. Finally, the area and the center of the object are
determined so that object’s motion to be tracked. The smartphone
application has been placed on a robot car and transmits by Bluetooth
to an Arduino assembly the motion directives so that to follow
objects of a specified color. The experimental evaluation of the
proposed algorithm shows reliable color detection and smooth
tracking characteristics.", keywords = "Android, Arduino Uno, Image processing, Object
motion detection, OpenCV library.", volume = "9", number = "4", pages = "999-4", }