Intelligent Detection of Convex Polygon Based on Hough Transformation and Set Classifier
Xudong Yang, Peng Dai, Ping He, Pan Li · 2010
This paper proposes a shape recognition method for detecting convex polygons (CVPs) in image planes, which is characterized by using Hough transformation (HT) and designing a set classifier. HT is used to extract the sides of a CVP by searching the peaks of accumulators in the Hough Parametric Space (HPS). A total set of the intersection points formed by all sides of CVP and their extending lines can be established based on the peaks in HPS, which includes a subset only containing the vertex of CVP. Based on the gradient distribution of the elements in the subset, the classifier for extracting the subset is designed. Compared with conventional method, the detection method has advantage of detecting the CVP shape with discontinuity and broken edges, and thus worthy of being promoted.