Watersheds are one of the classics problems in topography. Its definition in topography is the ridge or upland between two basins. Figuratively, a drop of water falling in one side of this line flows down until it reaches one lake, river or ocean, whereas a drop falling on the other side flows down to other ocean. The two regions which watershed line separates call the catchment basin, the two ...

This paper introduces a watershed-based stochastic segmentation methodology. The approach is based on using M realizations of N random markers to build a probability density function (pdf) of contours which is then segmented by volumic watershed for de ning the R most signi cant regions. It over-performs the standard watershed algorithms when the aim is to segment complex images into a few regi...

In this paper a marker-controlled and regularized watershed segmentation is proposed. Only a few previous studies address the task of regularizing the obtained watershed lines from the traditional markercontrolled watershed segmentation. In the present formulation, the topographical distance function is applied in a level set formulation to perform the segmentation, and the regularization is ea...

The watershed transform is a very powerful segmentation tool which comes directly f rom the idea of watershed line in geohydrology. It has proved its e f ic iency in many computer vision application $fields. Th i s paper presents a new implementation of the watershed which is optimal according to computation, t ime. The flooding algorithm is reminded. Then , a massively parallel cellular automa...

This study explored the application of a multi-objective evolutionary algorithm (MOEA) and Pareto ordering in the multiple-objective automatic calibration of the Soil and Water Assessment Tool (SWAT). SWAT was calibrated in the Calapooia watershed, Oregon, USA, with two different pairs of objective functions in a cluster of 24 parallel computers. The non-dominated sorting genetic algorithm (NSG...

Watershed Transformation in mathematical morphology is a powerful tool for image segmentation. Watershed transformation based segmentation is generally marker controlled segmentation. In the last decade medical image processing is immerged as one of the major area of research .In medical science, Magnetic Resonance Imaging(MRI) is a very popular technique used in details.MRI provides good contr...

There are two conceptually distinct methods for computing watershed transform in digital images, namely the traditional immersion based simulation and rainfall simulation. The traditional watershed algorithm is usually implemented by simulating a flooding through immersion. The immersion simulation process starts with piercing holes in each minima (LIM), then this surface is gradually immersed ...

With the rapid developments of higher resolution imaging systems, larger image data are produced. To process the increasing image data with conventional methods, the processing time increases tremendously. Image segmentation is one of the many image processing algorithms, and it is widely used in medical imaging (i.e. find tumor in MRI), robotic vision (i.e. vision-based navigation), and face r...

Watershed transformation is a common technique for image segmentation. However, its use for automatic medical image segmentation has been limited particularly due to oversegmentation and sensitivity to noise. Employing prior shape knowledge has demonstrated robust improvements to medical image segmentation algorithms. We propose a novel method for enhancing watershed segmentation by utilizing p...

The collapsed buildings due to earthquake were detected from post-event aerial images using watershed segmentation algorithm. The objective was to detect the collapsed buildings based on the analysis of the cast shadows. The building boundaries were available and stored in a GIS as vector polygons. The building polygons were utilized to perform assessments in a building specific manner. The app...