Hough transform-based cubic spline recognition for natural shapes Online publication date: Mon, 25-Feb-2019
by Cheng-Huang Tung; Wei-Jyun Syu; Wei-Cheng Huang
International Journal of Computational Science and Engineering (IJCSE), Vol. 18, No. 2, 2019
Abstract: A two-stage GHT-based cubic spline recognition method is proposed for recognising flexible natural shapes. First, the proposed method uses cubic splines to interpolate a flexible natural shape, and a sequence of connected boundary points is generated from the cubic splines. Each such point has accurate tangent and curvature features. At the first recognition stage, the proposed method uses the modified GHT to adjust the scale and orientation factors of the input shape with respect to each reference model. At the second recognition stage, the proposed point-based matching technique calculates the difference between each specific reference model and its corresponding adjusted input shape at the point level. In experiments for recognising 15 categories of natural shapes, including fruits and vegetables, the recognition rate of the proposed two-stage method is 97.3%, much higher than 79.3% measured by the standard GHT.
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