Journal of the Korean Geophysical Society (지구물리)

Korean Society of Earth and Exploration Geophysicists (한국지구물리·물리탐사학회)
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3D Object Recognition Using SOFM

3D Object Recognition Using SOFM

  • Published : 20060000
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Abstract

3D object recognition independent of translation and rotation using an ultrasonic sensor array, invariant moment vectors and SOFM(Self Organizing Feature Map) neural networks is presented. Using invariant moment vectors of the acquired 16×8 pixel data of square, rectangular, cylindric and regular triangular blocks, 3D objects could be classified by SOFM neural networks. Invariant moment vectors are constant independent of translation and rotation. The recognition rates for the training and testing data were 95.91% and 92.13%, respectively.

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References

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