Shape recognition based on wavelet-transform modulus maxima

Faouzi Alaya Cheikh, Azhar Quddus, Moncef Gabbouj

Abstract: In this paper we propose a new approach to object recognition based on the polygonal approximation of the object contour. The vertices of the polygon are the high curvature points of the contour, selected using the wavelet transform modulus maxima. We associate with this shape description a simple measure to estimate the similarity between objects. The description scheme and the similarity measure proposed take into consideration the way the human visual system perceives objects and compares them. The description scheme and the similarity measure can be used in several applications such as content-based indexing and retrieval, evaluation of segmentation results in the context of MPEG-4, or in classical classification problems. The proposed scheme is invariant to translation, rotation, scale change and noise corruption. Moreover, this description scheme allows accurate reconstruction of the shape boundary from the feature vector used to describe it. The experimental results and comparisons show the performance of the proposed technique.