Watershed transform is a classical method of image segmentation in mathematical morphology. This method

with a wide perspective

has been applied successively into some fields like remote sensing images processing of satellite and radar

biomedical and computer vision applications. Watershed transform is a relatively time consuming task

and the study of this problem has been disesteemed by researchers for its low efficiency. But also for this reason

there appear some new theories and algorithms; moreover

with the development of parallel tools

watershed transform has an increasing attention internationally. As to the resent literatures on this field

variety of formalizing model makes the definition

algorithm and implementation of watershed lack in uniform description. Pointing to this status this paper starts with a rigorous definition of watershed transform for continuous case

followed by two kinds of representative definitions for digital case. The solution of plateau problem is discussed in detail. Then some new watershed algorithms proposed in recent years are classified and analyzed

including watershed algorithms by immersion and by topographical distance. The need to distinguish between definition

algorithm specification and algorithm implementation is pointed out. Finally we present the problems and challenges of future research

including accuracy of watershed transform

problem of over-segmentation

parallelization of algorithms and so on.