Structuring element

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

Properties of Morphological Operators Applied to Analysis of ECG Signals

Abstract: In this paper, we evaluate a multiscale-filtering scheme based on the mathematical morphological theory. We show that opening and closing a signal with a gray scale operator can change the original signal in many ways depending on the shape and size of structuring element (SE). Within this framework, the problem of choosing an appropriate structuring element in ECG signal preprocessing is studied. Some theoretical results for morphological operators applied to analysis of ECG signals are derived. In order to obtain a measure of the performance of different structuring elements, we propose new filtering scheme and evaluate some tests with signals from MIT/BIH database.

An improved image coding algorithm using morphological operator theory

Abstract: A new algorithm for exact reconstruction of an original image from its morphological skeleton and edge structure is presented. The new technique results in improved computational performance and reduced memory storage requirements. The algorithm is also shown to have better performance characteristics than two previous algorithms in terms of data storage, data transmission rate, and computational complexity. If the size of the maximal element of a skeleton point is larger than the size of a unit structuring element, the algorithm will result in at least a 25% computational savings. The computational savings increases nonlinearly as the size of the maximal element increases. >

X-ray bone fracture subtraction using geodesic active contour and mathematical morphology operations

Abstract: This paper presents a new approach on deformable models that combines geodesic active contour model with mathematical morphology operations and minimum path-finding algorithms. Morphology operations are applied to define the constraints of the geodesic active contour model. The size and shape of the structuring element for morphology operations describe a local window that collect and filter the local image gradient information. This local information is fed to the global constraints of the energy function of the geodesic active contour. The focus of this research is to investigate the optimal constraints that allow the model to be able to perform the segmentation task of the bone fracture subtraction of X-ray image of human arms over a noisy cast background. The model developed in this project speeded up the method of geodesic active contour, improved the result of the edge finding by minimizing the energy function based on a local window and avoided the curve attracted to the small gaps on the weak edges to improve the accuracy of segmentation.

Rotationally invariant pecstrum: A rotationally invariant object descriptor based on mathematical morphology

Abstract: Mathematical morphology is becoming increasingly important in industrial vision applications for object recognition and defect inspection. In this paper we define a new function based on mathematical morphology, which we named the Rotationally Invariant Pecstrum (RIP). The RIP is proven to be invariant under rotation regardless of the shape of the structuring element. This paper also discusses how to use the RIP as an object descriptor and studies the effect of using different structuring elements on recognizing objects of different shapes.

Morphological Operator Distributions Based On Monotonicity And The Problem Posed By Digital Disk-Shaped Structuring Elements

Abstract: A sequence of structuring elements S = {S1,...,SN} is said to be increasing if it has the property that for each i, Si+i ⊃ Si. In general, such sequences are made up of elements with similar shapes but different sizes; e. g., lines, squares, octagons, and disks. A morphological operation ψ is said to be monotonic with respect to an Increasing structuring element sequence S, if, for any set X, either: (X 'F Si+1) 2 (X 'F Si), Vi (Monotonic increasing) Or (X AIF Si) 3 (X III Si+1), Vi (Monotonic decreasing) Dilation is monotonic increasing while erosion is monotonic decreasing. These properties make it possible to unambiguously classify every pixel in a binary image by associating each with one of the elements in the sequence S. Morphological openings and closings are also monotonic, but only if an additional property holds for the sequence 5, namely, that for each i, there exists a structuring element T such that Si+1 = (Si ⊕ T), or in other words, Si and Si+1 must be similar in shape up to a dilation. In the digital world, squares, hexagons, and octagons are similar but digital approximations to disks are not. This poses problems for trying to generate morphological shape and size distributions based on very accurate digital disks. This paper proves the monotonicity properties for erosions, dilations, openings, and closings, and shows how pixel distributions or classifications based on shape can be generated from these properties. It also discusses the problem posed by digital disks, and describes one method of circumventing it.© (1988) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.