Extracting geometric information from images with the novel Self Affine Feature Transform
Abstract
Based on our research, the Self Affine Feature Transform (SAFT) was introduced as it extracts quantities which hold information of the edges in the investigated image region. This paper gives details on algorithms which extract various geometric information from the SAFT matrix. As different image types should be analysed differently, a classification procedure must be performed first. The main contribution of this paper is to describe this classification in details. Information extraction is applied for solving different 2-dimensional image processing tasks, amongst them the detection of convergent lines, circles, ellipses, parabolae and hiperbolae or localizing corners of calibration grids in a robust and accurate manner.
Keywords:
SAFT, feature extraction, affine invariance, optical flow, classificationHow to Cite
Prohászka, Z., Lantos, B. “Extracting geometric information from images with the novel Self Affine Feature Transform”, Periodica Polytechnica Electrical Engineering, 53(3-4), pp. 163–178, 2009. https://doi.org/10.3311/pp.ee.2009-3-4.08
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