Strategies for image segmentation combining region and boundary information

Image segmentation has been, and still is, an important research area in Computer Vision, and hundreds of segmentation algorithms have been proposed in the last 30 years. However, elementary segmentation techniques based on either boundary or region information often fail to produce accurate segmentation results on their own. In the last few years, there has therefore been a trend towards algorithms that take advantage of their complementary nature. This paper reviews various segmentation proposals that integrate edge and region information and highlights different strategies and methods for fusing such information. The key objective is to point out the advantages and disadvantages of the various approaches, as well as to comment upon new and interesting ideas that perhaps have not been properly exploited.