Content-based object segmentation in video sequences

Motivated by the emerging video coding standard MPEG-4, this paper proposes a solution to address the problems of unsupervised object segmentation in images and video sequences, using color information. Although the human visual system is very sensitive to edge information, image segmentation is one of the most fundamental and yet complex tasks in image processing. The correct classification of different elements in a scene into different objects and the accurate extraction of their contours is crucial, since the performance of an object-tracking algorithm relies mainly on the segmentation results. In this paper we propose a novel algorithm for unsupervised object segmentation based on the combination of a region growing algorithm, clustering and a morphological opening by reconstruction operator using the inherent color information present in the image, in order to create a robust segmentation tool.