Abstract
A new algorithm using invariant spectral features for segmenting colour images is presented in this paper. Input data are three primary images obtained from a colour sensor. The input colour image is transformed to IHS (Intensity, Hue, Saturation) colour space. This colour space transform compensates for illumination variations and delivers image pixel values with low variance for individual colour regions, hence contributing to simplified segmentation. The hue and saturation images are then separately filtered and combined. The resulting image is segmented by means of a threshold process. An opening operation on the segmented image completes the algorithm. Experimental results obtained for several images are presented. Issues related to illumination and sensors are also addressed.
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References
Ohta, Y., Kanade, T. and Sakai, T.: Colour information for region segmentation,Computer Graphics and Image Processing 13 (1980), 222–241.
Connah, D. M. and Fishbourne, C. A.: The use of colour information in industrial scene analysis, inProc. 1st Int. Conf. on Robot Vision and Sensory Controls, Stafford-on-Avon, UK, 1981, pp. 340–347.
Huntsberger and Delxazi, M. F.: Color edge detection,Pattern Recognition Lett. 3 (1985), 205–209.
Barth, M., Parthasarathy, S., Wang, J., Hu, E., Hackwood, S. and Beni, G.: A colour machine vision for microelectronics: application to oxide thickness measurement, inProc. IEEE Int. Conf. on Robotics and Automation, San Francisco, USA, 1986, pp. 1242–1247.
Tominaga, S.: Colour classification method for colour images using a uniform colour space, inProc. IEEE Int. Conf. on Pattern Recognition, NJ, USA, 1990, pp. 803–807.
Jordan, J. R. and Bovik, A. C.: Computational stereo vision using colour, IEEE Control Systems Magazine8 (1988), 31–36.
Vlachos, T. and Constantinides A. G.: Graph theoretical approach to colour picture segmentation and colour classification,IEE Proc. Pt I,140 (1993), 36–45.
Pratt, W. K.:Digital Image Processing, Wiley, New York, 1991.
Flory, E.: Image acquisition technology,IEEE Proc. 73 (1986), 613–637.
Ledley, R. S., Buas, M. and Golab, T. J.: Fundamentals of true colour image processing, inProc IEEE Int. Conf. on Pattern Recognition, NJ, USA, 1990, pp. 790–799.
Papoulis, A.: Probability, Random Variable and Stochastic Processes, McGraw-Hill, New York, 1989.
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Andreadis, I., Tsalides, P. Coloured object recognition using invariant spectral features. J Intell Robot Syst 13, 93–106 (1995). https://doi.org/10.1007/BF01664757
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DOI: https://doi.org/10.1007/BF01664757