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A new approach to object classification in binary images

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2 Author(s)
Randolph, T.R. ; Center for Signal & Image Process., Georgia Inst. of Technol., Atlanta, GA, USA ; Smith, M.J.T.

In this paper, we address the problem of classifying binary objects using a cascade of a binary directional filter bank (DFB) and a higher-order neural network (HONN). The binary DFB receives as input a binary image and returns as output a binary subband representation. Because processing is performed on a finite field, the DFB is able to operate efficiently. Furthermore, the DFB provides a representation that delineates the directional components in the image, which enables the HONN to exploit the underlying shape of the object effectively. The paper provides a description of the new binary DFB and its use with the HONN, all in the context of object classification

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Electronics, Circuits and Systems, 2000. ICECS 2000. The 7th IEEE International Conference on  (Volume:1 )

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