Shape Recognition with Generalized Beam Angle Statistics

Abstract

In this study, we develop a new shape descriptor and a matching algorithm in order to find a given template shape in an edge detected image without extracting the boundary. The shape descriptor based on Generalized Beam Angle Statistics (GBAS) defines the angles between the lines connecting each boundary point with the rest of the points, as random variable. Then, it assigns a feature vector to each point using the moments of beam angles. The proposed matching algorithm performs shape recognition by matching the feature vectors of boundary points on the template shape and the edge pixels on the image. The matching process also considers the spatial distance of the edge pixels. The experiments performed on MPEG-7 data set show that the template shapes are found successfully on the noisy images.