Computer vision is a growing field in the image
processing domain. There are numerous applications associated
with this field and it is growing fast. One of the important
metric in such field is object detection and tracking. The aim of
this paper is to build an object tracking system using colour
image processing. There are many methods used for the tracking
of a coloured object. One of the novel algorithms for object
detection is developed on the basis of all the methods studied.
Target object is an object having the user desired colour form
and it can be in any shape. As the area here is of colour image
processing, the amount of resolution of a camera required is
high so that a clear algorithm may be applied to the target
object.
Published In : IJCAT Journal Volume 2, Issue 2
Date of Publication : 28 February 2015
Pages : 27 - 30
Figures :03
Tables : --
Publication Link :Real-Time Object Tracking and Color Detection Using
Color Feature
Nikhil Kumar : M.Tech Scholar,CSE Department, SIRT, Bhopal
Deepak Choudhary : Faculty of CSE Department, SIRT, Bhopal
Hue
Chromaticity
Luminance
Kernel
Spectrum
Grayscale
A robust and efficient automated single object tracking
system is presented. The system has been implemented
using an algorithm based on point to point manipulation
and color identification. The algorithm has
experimentally been shown to be quite accurate and
effective in detecting a single moving color object. A
novel algorithm for coloured object tracking is proposed
herewith using a particular colour model (which is RGB
colour model), and it is successfully simulated and
verified. The proposed technique can be extended and
used in fields like Robotics, Computer Vision, etc.
[1] Rafael C. Gonzalez, Richard E. Woods. (2002): Digital
Image processing, Second Edition. Prentice Hall
International
[2] Yali Amit, 2D object detection and recognition - models
algorithms and networks.
[3] Hugh L. Kennedy, “Detecting and tracking moving
objects in sequences of color images”, Pacific Noise and
Vibration (PNV) Pty. Ltd.
[4] Muhammad Owais Mehmood, “Study and
Implementation of Color-based Object Tracking in
Monocular Image Sequences”, 2009 proceedings IEEE
Transactions.
[5] A. Yilmaz, O. Javed, and M. Shah, "Object tracking: A
survey," ACM Comput. Surv., vol. 38, no. 4, pp. 13+,
2006. [Online]. Available:
http://dx.doi.org/10.1145/1177352.1177355
[6] D. Comaniciu and P. Meer, "Mean shift: a robust
approach toward feature space analysis," Pattern
Analysis and Machine Intelligence, IEEE Transactions
on, vol. 24, no. 5, pp. 603-619, 2002. [Online].
Available: http://dx.doi.org/10.1109/34.1000236
[7] G. R. Bradski, "Computer vision face tracking for use in
a perceptual user interface," Intel Technology Journal,
no. Q2, 1998. [Online]. Available:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1
.14.7673
[8] PATRICK MARCHAND and O. T HOMAS HOLLAND:
Graphics and GUIs with MATLAB, Third Edition
[9] Hong-Ying Shen; Shui-Fa Sun; Xian-Bing Ma; Yi-Chun
Xu; Bang-Jun Lei, "Comparative study of colour feature
for particle filter based object tracking,", 2012
International Conference on Machine Learning and
Cybernetics (ICMLC), vol.3, no., pp.1104,1110, 15-17
July 2012
