Real-time colour classification for preprocessing photogrammetry images

Robert Massen; Gerhard Volk

doi:10.1117/12.2294280

1 August 1990 Real-time colour classification for preprocessing photogrammetry images

Robert Massen, Gerhard Volk

Proceedings Volume 1395, Close-Range Photogrammetry Meets Machine Vision; 139511 (1990) https://doi.org/10.1117/12.2294280
Event: Close-Range Photogrammetry Meets Machine Vision, 1990, Zurich, Switzerland

Abstract

The automatic processing of stereo images for 3D information extraction can be simplified by colour classification of the stereo image pairs prior to the correlation matching procedures. The number of corresponding pixels to be matched is drastically reduced, if only those pixels on the epipolar line are correlated which belong to the same class of colours. Colour classes of natural scenes like aerial photographies are usually composed of complicatedly shaped clusters which makes the manual setting of RGB classifier parameters an almost impossible task. We present a real-time IHS-colour classification system which uses neural network principles based on self-organizing look-up-tables for learning typical colour classes . A learning rule for the supervised training of this LUT classifier is presented . The proposed LUT classifier shows all the positive features of a 3-layer perceptron Neural Network, but performs 70.000 times faster then a simulated perceptron network and uses low-cost, commercially avai- lable components. The height measurement of plantlets for the automation in greenhouses is presented as a typical application of these principles.

Citation Download Citation

Robert Massen and Gerhard Volk "Real-time colour classification for preprocessing photogrammetry images", Proc. SPIE 1395, Close-Range Photogrammetry Meets Machine Vision, 139511 (1 August 1990); https://doi.org/10.1117/12.2294280

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