In this paper we present a new implementation of a rainfalling watershed segmentation algorithm. Our previous algorithm was a one-run algorithm. All the steps needed to compute a complete watershed segmentation were done in one run over the input data. In our new algorithm we tried another approach. We separated the watershed algorithm in several low-complexity relabeling steps that can be perf...

In this paper, a formal de"nition and a new algorithmic technique for the watershed transformation is presented. The novelty of the approach is to adapt the connected component operator to solve the watershed segmentation problem. The resulting algorithm is independent of the number of grey-levels, employs simple data structures, requires less error prone memory management, and issues a lower c...

The watershed transformation is a popular image segmentation algorithm for grey scale images. In this paper, we present a deenition of the watershed segmentation, based on sets of neighboring pixels. The deenition is consistent with the behavior of most implementations of the watershed algorithm which do not construct watersheds lines, namely, to chose one arbitrary label in the case of competi...

The goal of segmentation is to partition an image into disjoint regions. In this paper, the segmentation problem based on partition clustering is viewed as a combinatorial optimization problem. A new algorithm called a quantum evolutionary clustering algorithm based on watershed (QWC) is proposed. In the new algorithm, the original image is first partitioned into small pieces by watershed algor...

Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful technology for separating complex samples. The typical goal of GC×GC peak detection is to aggregate data points of analyte peaks based on their retention times and intensities. Two techniques commonly used for two-dimensional peak detection are the two-step algorithm and the watershed algorithm. A recent study [4] compared t...

Best Management Practices (BMPs) are implemented in a watershed to reduce the amount of non-point source pollutants transported to water bodies. However, an optimization algorithm is required to choose the efficient type, size, and location of BMPs for application in a watershed for improving the water quality. In this study, the Charged System Search, a well-known and powerful meta-heuristic o...

In this paper, we present a fast watershed algorithm based on the rainfalling simulation. We present the various techniques and data structures utilized in our approach. Throughout this work, the processing of large data sets (images as well as volume data) is especially emphasized. The results’ correctness, the fast execution time, and the memory requirements are discussed in detail. First we ...

Medical Image segmentation deals with segmentation of tumor in CT and MR images for improved quality in medical diagnosis. Geometric Vector Flow (GVF) enhances the concave object extraction capability. However, it suffers from high computational requirement and sensitiveness to noise. This paper intends to combine watershed algorithm with GVF snake model to reduce the computational complexity, ...

Watershed segmentation/transform is a classical method for image segmentation in gray scale mathematical morphology. Nevertheless watershed algorithm has strong recursive nature, so straightforward parallel one has a very low efficiency. Firstly, the advantages and disadvantages of some existing parallel algorithms are analyzed. Then, a Further Optimized Parallel Watershed Algorithm (FOPWA) is ...

Watershed segmentation/transform is a classical method for image segmentation in gray scale mathematical morphology. Nevertheless watershed algorithm has strong recursive nature, so straightforward parallel one has very low efficiency. Firstly, the advantages and disadvantages of some existing parallel algorithms are analyzed. Secondly, a Further Optimized Parallel Watershed Algorithm (FOPWA) i...