MSU Graphics & Media Lab
Image segmentation is an inherent part of important image processing applications like automated medical images analysis and photo editing. Also, a wide range of computational vision problems could benefit from existence of reliable and efficient image segmentation technique. For instance, intermediate-level vision problems such as shape from silhouette, shape from stereo and object tracking in video could make use of reliable segmentation of the object of interest from the rest of the scene. Higher-level problems such as recognition and image indexing can also make use of segmentation results in matching.
Fully automated segmentation techniques are being constantly improved, however, current state-of-the art is such that no automated image segmentation technique can be applied fully autonomously with reliable results in general case. That is why semi-automatic segmentation techniques that allow solving moderate and hard segmentation problems by modest interactive effort on the part of the user are becoming more and more popular.