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Coloured object recognition using invariant spectral features

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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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Authors and Affiliations

  1. Laboratory of Electronics, Division of Electronics and Information Systems Technology Democritus University of Thrace, 67100, Xanthi, Greece

    I. Andreadis & Ph. Tsalides

Authors
  1. I. Andreadis
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  2. Ph. Tsalides
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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

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