Voronoi based face segmentation

Abstract

Image segmentation, decomposition of a gray level or color image into homogeneous tiles, is arguably the most important low-level vision task. Homogeneity is usually defined as similarity in pixel values. Segmentation is a fundamental process in digital image processing which has found extensive applications in areas such as content-based image retrieval, medical image processing, and remote sensing image processing. Its purpose is to extract labeled regions or boundaries for targeted objects for subsequent processing such as surface description and object recognition. A segmentation procedure usually consists of two steps. The first step is to choose a proper set of features which can identify the same-content regions and meanwhile differentiate different-content regions; the second step is to apply a segmentation method to the chosen features to achieve a segmentation map” (Deng H. and Clausi D., 2004).