Zero crossings of a non-orthogonal wavelet transform for object location

In this paper we address the task of segmentation of objects from photographs. A method of extraction of features based on the zero-crossings of a wavelet transform is described. The wavelet transform basis functions are derived from the second derivative of a gaussian function. The extracted features are then used in a multilevel hypothesis generate and test algorithm to locate the objects of interest. The matching algorithm is based on the springs and templates framework of Fischler and Eschlanger [1]. The zero-crossings of the wavelet coefficients at different scales are combined in the model-matching stage to generate possible candidates. We apply this method to segment human faces from newspaper photographs.