Structuring element

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

A smoothing method of lofargram using morphological opening filter (part 3)

Abstract: Lofargram is a processing method for analyzing the temporal structure of passive sonar signals by spectral analysis. The authors have proposed to suppress the impulse noise on lofargram using morphological opening filter instead of averaging procedure which has been used generally. In our experimental results, the effective improvements of the processing gain and the time resolution have been obtained as compared with averaging procedure.However, a large amount of the calculation time of morphological opening filter occurred by the memory access bottleneck with software implementation has been an obstacle to the real-time processing. In this paper, the parallel algorithm of morphological opening filter for lofargram using the distributivity by the structuring element is proposed for the high speed calculation. This algorithm is inspected by the execution results using MIMD parallel machine. Then, the limitation of this method and the performance of the processor node for the real-time smoothing of lofargram are estimated.

Morphological structuring image decomposition

Abstract: Two major structuring element decomposition techniques are compared, and the superiority of the two pixel decomposition techniques over the cellular decomposition technique is shown in terms of the number of pipeline stages. As for the general structuring function decomposition, to the authors' knowledge, there is no efficient algorithm that has been found. The difficulty can be overcome by using an adequate representation of the general gray-scale structuring function. Representing a gray-scale image as a specific 3-D set, i.e. an umbra, makes it easier to shift all morphological theorems from the binary domain to the gray-scale domain; however, a direct umbra representation is not appropriate for the general gray-scale structuring function decomposition. The authors also provide a morphologically realizable representation and decomposition for the general gray-scale structuring function and show recursive algorithms which are pipelineable for efficiently performing gray-scale morphological operations. >

Gray Morphology Filtering for Wood Defect Images

Abstract: This paper first defined gray morphology filtering methods based on mathematical morphology, followed with examples of a wood defect image treated before and after open, as well as closed, filtering treatments. By observing the sectional gray distribution of the wood defect image, the effects of the filtering treatments were determined. Results found that gray morphology filtering could effectively remove noise in wood defect images, improve image vision and heighten accuracy for edge detection. The results verified the feasibility of applying gray morphology filtering to treat wood defect images.

Optimal multiresolution morphological image processing

Abstract: The problem of selecting the pyramid level for optimal morphological processing of an image with a selected structuring element is considered. Each level in the image pyramid is eroded by a structuring element and the residue computed. The residues for all pyramid levels are normalized and compared in order to determine the optimal image pyramid level. A method for residue normalization considering the fundamental morphological operation, erosion, is presented. An optimal structuring element can be determined at the selected pyramid level on the basis of minimal residues, providing as complete a representation of the image as possible. >

Disturbance detection using an improved hit-or-miss transform

Abstract: Power disturbances have always been an important issue in the power system protection. This paper presents a novel algorithm, improved hit-or-miss transform (IHMT), for the detection of power disturbances. IHMT is a morphological operator that uses a structuring element (SE) consisting of two sets. Besides, it employs basic morphological operators only, which ensures the algorithm to perform fast calculation. Applied to power systems, IHMT detects the location and duration of disturbances. A variety of power disturbances have been simulated to evaluate the validity of IHMT.