Image segmentation by mathematical morphology is a methodology based upon the notions of watershed and homotopy modification. This paper aims at introducing this methodology through various examples of segmentation in materials sciences, electron microscopy and scene analysis. First, we define our basic tool, the watershed transform. We show that this transformation can be built by implementing...

This paper proposes, a method modified Gradient image as input to the watershed transform algorithm this is compared with Fast Level Set method. The method is feasible in medical imaging and deserves. It could be used to segment the white matter, brain tumor and other small and simple structured organs in CT and MR images. In this paper used Gradient watershed transform and Fast Level Set metho...

In this paper we introduce a new method for image segmentation. It is based on a height map generated from the input image. The height map characterizes the image content in such a way that the application of the watershed concept provides a proper segmentation of the image. The height map enables the watershed method to provide better segmentation results on difficult images, e.g., images of n...

We developed a completely automated technique for carotid wall segmentation and intima – media thickness (IMT) measurement in ultrasound images based on the watershed transform. Morphological operators are used to extract the foreground markers for performing marker-based watershed segmentation. The watershed basin containing the carotid artery is automatically extracted. The far wall of the ar...

The Fast watershed transform is an innovative approach that detects salient objects in an image. This transformation is entirely different from traditional watershed as it doesn’t depend on mathematical morphology. The flooding of water in the image is efficiently simulated using the FIFO queue of pixels. It starts with sorting image pixel according to their intensity levels and stores them in ...

Watershed from markers and hierarchical watershed are approaches suitable for interactive image segmentation: in the former, the user can edit markers to control the segmentation result; in the latter, the user can select an image partition from a nested set of partitions. We propose an interactive image segmentation tool that allows transition from one approach to other and thus the combinatio...

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...

SAR images data are the result of a coherent imaging system that produces the speckle noise phenomenon. Image segmentation is the process of separating or grouping an image into different parts. The good performance of recognition algorithms depend on the quality of segmented image. An important problem in SAR image application is correct segmentation. In this paper, we consider the problem of ...

This paper deals with region based watershed segmentation for developing “MemberingFilters”.Watershed transformation is a common technique for image segmentation. Region based segmentation classify a particular image into a number of regions or classes. Region-based segmentation methods attempt to partition or group regions according to Intensity values from original images, Textures or pattern...