Wavelet Descriptors for Object Recognition using Mexican Hat Function

Authors:	Nabout Adnan Abou, University of Wuppertal, Germany Tibken Bernd, University of Wuppertal, Germany
Topic:	1.1 Modelling, Identification & Signal Processing
Session:	Image Processing and Biomedical Applications
Keywords:	Image Processing, Object Recognition, Feature Extraction, Fourier Transformation, Wavelet Transformation

Abstract

In this paper, we propose an object recognition method for 2D objects using wavelet descriptors. The descriptors are derived from the continuous wavelet transform using the Mexican hat function as mother wavelet. In contrast to the other known methods we apply an angle function to describe object contours extracted as polygons. The contour extraction is based on the object oriented contour extraction method (OCE). The polygon representation is based on the curvature dependent contour approximation (CDCA). The continuous wavelet transform (CWT) is used in order to apply a suitable number of wavelet descriptors (WD), which are qualified to characterize the object shapes.