To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those ...

[1] A new global optimization algorithm, dynamically dimensioned search (DDS), is introduced for automatic calibration of watershed simulation models. DDS is designed for calibration problems with many parameters, requires no algorithm parameter tuning, and automatically scales the search to find good solutions within the maximum number of user-specified function (or model) evaluations. As a re...

Watershed transform has interesting properties that make it useful for much different image segmentation analysis, it has important drawbacks (Over segmentation, sensitivity to noise, poor detection of thin or low signal to noise ratio structures). Recent advances in medical imaging technology using multiple Computed tomographies (CT) provide volumetric datasets with spatial resolution segmenta...

A combination of K-means, watershed segmentation method, and Difference In Strength (DIS) map was used to perform image segmentation and edge detection tasks. We obtained an initial segmentation based on K-means clustering technique. Starting from this, we used two techniques; the first is watershed technique with new merging procedures based on mean intensity value to segment the image regions...

A road segmentation technique is proposed based on a mathematical morphology tool called watershed transform. Starting from a coarse marker of the road to be segmented, we modify the gradient image of the scene and compute the watershed transform of this image. The result provides a fair segmentation of the road. The marker itself is produced by using the watershed transform, and a simplified r...

The stochastic watershed is an unsupervised segmentation tool recently proposed by Angulo and Jeulin. By repeated application of the seeded watershed with randomly placed markers, a probability density function for object boundaries is created. In a second step, the algorithm then generates a meaningful segmentation of the image using this probability density function. The method performs best ...

The comprehensive and systematic management of watersheds is essential for reducing the adverse environmental impacts arising from anthropogenically caused erosion and subsequent sedimentation. This paper describes a computational methodology that is designed to serve as a watershed decision support system and is capable of controlling environmental impacts of non-point source pollution resulti...

The watershed transformation is a powerful tool for segmenting images, but its precise deenition in discrete spaces raises diicult problems. We propose a new approach in the framework of orders. We introduce the tesselation by connection, which is a transformation that preserves the connectivity, and can be implemented by a parallel algorithm. We prove that this transformation possesses good ge...

We propose an original approach to the watershed problem, based on topology. We introduce a “one-dimensional” topology for grayscale images, and more generally for weighted graphs. This topology allows us to precisely define a topological grayscale transformation that generalizes the action of a watershed transformation. Furthermore, we propose an efficient algorithm to compute this topological...

Introduction The morphologic features of human sperms are key indicators for monitoring fertility problems in men. Therefore, automated analyzing methods via microscopic videos have become the most favorite policy in infertility treatment during the last decades. Materials and Methods In the proposed method, firstly a hypothesis testing framework was defined to distinguish sperms from backgroun...