Abstract
We review a previously presented proposal – Geometric Texton Theory (GTT) – that feature categories naturally arise through consideration of the maximum likelihood explanations for image measurements by gaussian derivative filters. We present results relevant to this proposal for the case of 1-D measurement by filters of 0th, 1st and 2nd order. The results are consistent with GTT.
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Griffin, L.D., Lillholm, M. (2005). Image Features and the 1-D, 2nd Order Gaussian Derivative Jet. In: Kimmel, R., Sochen, N.A., Weickert, J. (eds) Scale Space and PDE Methods in Computer Vision. Scale-Space 2005. Lecture Notes in Computer Science, vol 3459. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11408031_3
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DOI: https://doi.org/10.1007/11408031_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25547-5
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