Structuring element

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

An Adaptive Edge Detector Using Soft Mathematical Morphology

Abstract: In this paper, a novel adaptive soft morphological Laplacian (ASML) filter is proposed, based on a combination of the ideas of the soft morphological filtering and the Laplacian operator. ASML filter is an adaptive nonlinear edge detector. The adaptivity is achieved by employing four directional structuring elements and the dynamic repetition parameter. ASML filter has the capability of selecting the directional structuring element with the maximum response, whose direction varies depending on the change of directional edges. In addition, by replacing the Laplacian operator with soft morphological one, the ASML filter provides an alternative algorithm for edge detection and noise suppression. The experimental results show that the ASML filter outperforms the traditional edge detector in the two aspects

Multiple Attenuation Based on Mathematical Morphology Filtering Method

Abstract: Multiple attenuation is a troublesome problem in many seismic exploration areas. Current multiple suppression technique include two kinds of method: filter-based method and prediction-based method. However, these methods are powerless when the energy of multiples and primaries are mixed. Therefore, we introduce mathematical morphology method to seismic exploration as a new method to solve this problem. We found that multiples have similar seismic wavelet with that of primary reflection, and also have distinct seismic event. These seismic events give us a chance to distinguish the multiples and the primary reflections. Morphological filter is based on multiscale decomposition method. It use different structuring element to separate the multiples and the primary reflection clearly, and thus making multiple attenuation as well as saving subtle signal of primary reflection. In this abstract, we illustrate this method and give an examples of its application in synthetic and real data.

Fast Implementation of Gray-scale Morphological Matching Measurement

Abstract: This paper describes a fast algorithm for gray-scale image matching. This algorithm is based on the opening operation of mathematical morphology and presents a concept of morphological size in theory. By operating the morphological size of the discrepancy function between two gray-scale images, their matching degree can be measured well. By analyzing the sufficient condition to the result of that gray-scale image opened by 3-D sphere is non-empty in 3-D digital space, we adopted a technique of threshold decomposition to transform morphological operations from gray-scale to binary, which resolved the problems of difficult construction to 3-D structuring element and complex operations. A fast method of interval approximation was proposed to calculate the gray-scale morphological size quickly. Binary morphological operations use flat structuring elements and it is essentially boolean operations. Thus, this fast algorithm can be applied on the hardware platform well.

IR image signature of target detection based on the morphology filter with self-adaptive optimized genetic algorithms

Abstract: It is utilized the morphology filter and self-adaptive genetic algorithm to present the morphology filter with selfoptimized genetic algorithms (MFGA) for detecting IR image signature of the target. According to training the structuring element from original image data, some constraint conditions such as the prior knowledge and statistics laws , we summarize a judgment rule on finding out the best of structuring elements. As two special applications about IR image signature of the detections, one is detected solid thruster plume IR image and the other is weak-small infrared target under complex background. Compared the experimental results of the MFGA with those of the morphology filter (MF), we find that the MFGA has high convergence speed, greatly enhanced the Signal Noise ratio of target detection and effectively detecting target from complex background. And the experimental results and methods have a great significance in aerial forecasting and space defense.

Automatic selection of structuring element for object classification through morphology

Abstract: International conference on advances in pattern recognition and digital techniques : proceedings of P.C.Mahalanobis birth centenary volume(1993).