Image segmentation technology has been widely studied for a long time and many algorithms have already been developed and proven to be useful in practical applications. One approach that works well for one problem usually does not fit well to another problem in a slightly different domain. For example, in medical image segmentation, algorithms are usually classified in terms of imaging modalities such as CT, MRI or Ultrasound. Even in the same modality, current approaches often have to be based on the specific characteristics of different body tissues.
Segmentation approaches to medical and satellite images are certainly more incompatible.
Despite the huge efforts of years of research and development by numerous groups and individuals around the world, it is fair to say that there has been little significant breakthrough in the understanding of underlying principles of image segmentation. Instead of continuing to carry out research and development as have been done until now, many of which might have been heavily overlapped, we think it has come to the time to investigate some of the most fundamental issues in image segmentation, gain better insights into the problems we have encountered, and try to find out some new research directions in order to achieve a major breakthrough. We would like to raise the following questions as a starting point for discussions among the experts in this area, hoping to lead to a more comprehensive and common understanding of some fundamental issues in image segmentation. We think the best way to get started is to provide an opportunity for an in-depth discussion about the issues among the colleagues in image segmentation community. This motivates us to volunteer to organize an initial one-day workshop devoted solely for this purpose.