Structuring element

About: Structuring element is a research topic. Over the lifetime, 997 publications have been published within this topic receiving 26839 citations.

Topology-adaptive modeling of objects by using variable-size ball marching

Abstract: The paper proposes a novel method of modeling multiobject scenes or objects of arbitrary topology by a marching method based on mathematical morphology operations with a variable-size structuring element. We assume that 3D data on the whole object surface has been acquired. A narrow-band stopping region is built by merging the neighborhood of every data point. A single close-surface surrounding the data point set is given as an initial shape. The surface shrinks and splits smoothly by repeated erosions with a ball structuring element, whose size increases continuously as the curvature of the surface increases. Every surface point stops moving if it lies in the stopping region. After this surface fitting to the stopping region, the region is narrowed, and the fitting-and-narrowing cycle is repeated until the model is consistent with the object surface on the basis of a topological check. After the above rough estimation, for model refinement, we extract a quadrangular mesh from the resultant surface, and then perform precise fitting to the 3D data by using an energy minimisation.

Segmentation of Blood Vessels from Fundus Image Using Scaled Grid

Abstract: This paper proposes an automated technique to segment the retinal blood vessels from funduscopic images An Adaptive Line Structuring Element (ALSE) [12] is used for initial segmentation, but the process introduces large number of noisy objects accompanying the vessel structure Fortunately, these noisy objects are relatively isolated structures in comparison to the blood vessels So, a suitably Scaled Grid can be used to delimit the noisy objects from its neighborhood When an object falls fully inside a block of the grid, it is considered as a noise and is eliminated But the objects which passes over the boundary of a block are preserved The scale of the grid is iteratively increased to identify eventually the all isolated objects and are eliminated without any loss of the actual vessel’s structure To measure the performance, Accuracy, Sensitivity and Specificity are calculated and compared with the recently found algorithms proposed in the literature

Discrete algorithms for morphological filters in geometrical metrology

Abstract: In geometrical metrology, morphological filters are useful tools for the surface texture analysis and functional prediction. Although they are generally accepted and regarded as the complement to mean-line based filters, they are not universally adopted in practice due to a number of fatal limitations in their implementations —they are restricted to planar surfaces, uniform sampled surfaces, time-consuming and suffered from end distortions and limited sizes of structuring elements. A novel morphological method is proposed based on the alpha shape with the advantages over traditional methods that it enables arbitrary large ball radii, and applies to freeform surfaces and non-uniform sampled surfaces. A practical algorithm is developed based on the theoretical link between the alpha hull and morphological envelopes. The performance bottleneck due to the costly 3D Delaunay triangulation is solved by the divide-and-conquer optimization. Aiming to overcome the deficits of the alpha shape method that the structuring element has to be circular and the computation relies on the Delaunay triangulation, a set of definitions, propositions and comments for searching contact points is proposed and mathematically proved based on alpha shape theory, followed by the construction of a recursive algorithm. The algorithm could precisely capture contact points without performing the Delaunay triangulation. By correlating the convex hull and morphological envelopes, the Graham scan algorithm, originally developed for the convex hull, is modified to compute morphological profile envelopes with an excellent performance achieved. The three novel methods along with the two traditional methods are compared and analyzed to evaluate their advantages and disadvantages. The end effects of morphological filtration on open surfaces are discussed and four end effect correction methods are explored. Case studies are presented to demonstrate the feasibility and capabilities of using the proposed discrete algorithms.

A detail-preserving filtering module based on mathematical morphology

Abstract: Morphological filtering is a new and developing nonlinear filtering technique. The filtering principle of traditional morphological filters based on fitting the appointed structuring element to each objects of an image, which lead to damage image details seriously. So, this paper proposed a CS filtering model based on multiple structuring elements. Firstly use a contour-structuring element to extract the noise areas, and then use a connected structuring element to eliminate all the pixels in the noise areas at one time. This model distinguishes noise and valid objects by measuring objects' morphological extension. Many tests have been done to compare the filtering effect between the CS filtering model, the traditional morphological filters, Wiener filter and median filter. Experimental results indicate that the CS filtering model is really a detail-preserving filter.