Detection of curved edges at subpixel accuracy using deformable models
Kisworo, M., Venkatesh, S. and West, G. A. W. 1995, Detection of curved edges at subpixel accuracy using deformable models, IEE proceedings : vision, image and signal processing, vol. 142, no. 5, pp. 304-312.
One approach to the detection of curves at subpixel accuracy involves the reconstruction of such features from subpixel edge data points. A new technique is presented for reconstructing and segmenting curves with subpixel accuracy using deformable models. A curve is represented as a set of interconnected Hermite splines forming a snake generated from the subpixel edge information that minimizes the global energy functional integral over the set. While previous work on the minimization was mostly based on the Euler-Lagrange transformation, the authors use the finite element method to solve the energy minimization equation. The advantages of this approach over the Euler-Lagrange transformation approach are that the method is straightforward, leads to positive m-diagonal symmetric matrices, and has the ability to cope with irregular geometries such as junctions and corners. The energy functional integral solved using this method can also be used to segment the features by searching for the location of the maxima of the first derivative of the energy over the elementary curve set.
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Field of Research
080104 Computer Vision
Socio Economic Objective
890205 Information Processing Services (incl. Data Entry and Capture)
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