Affine invariant 2D recognition in grain classification

• Autorzy: Novakova K. , Kukal J.
• Języki publikacji: EN

Abstrakty

EN

Invariant recognition of 2D binary image often arises from image moments. They enable the construction of affine transform, which ensures the invariance to translation, scaling, first rotation and stretching of the image. It is a problem to ensure the invariance to the second rotation. The paper deals with two methods how to realize the affine invariant recognition system with the numerical stable elimination of the second rotation. Modified images are obtained via polar or Radon's transform. Mentioned two approaches enable affine invariant systems construction and they were used for analysis of particles in granular mixtures. The affine invariant system is applied to detail analysis of fertilizer grains.

Słowa kluczowe

EN

2D recognition; affine invariance; classification; grain analysis; vision

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2007
• Tom: Vol. 17, no. 2
• Strony: 135--144
• Opis fizyczny: Bibliogr. 2 poz.

Twórcy

autor

Novakova K.

autor

Kukal J.

• Czech Technical University in Prague, Faculty of Nuclear Sciences and Physical Engineering, Department of Software Engineering in Economy, Prague, Czech Republic

Bibliografia

• [1] T. Suk and J. Flusser, Affine Normalization of Symmetric Objects, Lecture Notes in Computer Science,3708, pp. 100-107,2005
• [2] T. Suk and J. Flusser, Graph method for genertaing affine moment invariants, Proc.ICPR 2004,IEEE Computer Society,pp. 192-195,2004