Topic
Structuring element
About: Structuring element is a research topic. Over the lifetime, 997 publications have been published within this topic receiving 26839 citations.
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TL;DR: In innovative algorithms to efficiently compute erosions and dilations of run-length encoded (RLE) binary images with arbitrary shaped structuring elements, the skeleton of the structuring element is extracted and the distance tables of the input image are built to speed up the calculations of the erosion and dilation operator.
Abstract: This paper presents innovative algorithms to efficiently compute erosions and dilations of run-length encoded (RLE) binary images with arbitrary shaped structuring elements. An RLE image is given by a set of runs, where a run is a horizontal concatenation of foreground pixels. The proposed algorithms extract the skeleton of the structuring element and build distance tables of the input image, which are storing the distance to the next background pixel on the left and right hand sides. This information is then used to speed up the calculations of the erosion and dilation operator by enabling the use of techniques which allow to skip the analysis of certain pixels whenever a hit or miss occurs. Additionally the input image gets trimmed during the preprocessing steps on the base of two primitive criteria. Experimental results show the advantages over other algorithms. The source code of our algorithms is available in C++.
1 citations
26 Oct 2012
TL;DR: The functionality of Gabor Wavelet with statistical features and Morphological filtering is addressed and the performance of the algorithms is evaluated to verify their efficiency in identifying the defective fabric image based on the segmented results.
Abstract: Automatic visual inspection is the backbone of any manufacturing industry. Manual inspections of textile fabrics are ineffective due to the fatigue and speed requirement. The Gabor wavelets network provides an effective way to analyze the input images and to extract the fabric features. This paper addresses the functionality of Gabor Wavelet with statistical features and Morphological filtering. The first method extracts statistical features of the input image using Gabor wavelet. Another method combines Gabor wavelet with morphological filtering to select appropriate structuring element. Finally, thresholding of the features are done to produce a binary image. In addition, the performance of the algorithms is evaluated to verify their efficiency in identifying the defective fabric image based on the segmented results.
1 citations
01 Nov 2013
TL;DR: Estimation of SE that can remove noise while preserving original signals is achieved by objective function that use Rank-Ordered Logarithmic Differences (ROLD) statistic for the impulse noise detection.
Abstract: In this paper, we propose an unsupervised design method for optimal structuring element (SE) of morphological filters. We formulate the design of SE as an optimization problem, and estimate an optimal shape and brightness of SE directly from degraded images. We estimated an optimal shape and brightness by using a Genetic Algorithm (GA). Estimation of SE that can remove noise while preserving original signals is achieved by objective function that use Rank-Ordered Logarithmic Differences (ROLD) statistic for the impulse noise detection.
1 citations
Journal Article•
TL;DR: In this method, histogram adjustment is adopted to enhance the signal-cluster-ratio, and hit-miss transform is used to get the suspicious targets.
Abstract: It is hard to detect the dim small target with few pixels and low intensity in the image of complex background.According to the intensity features of dim small target,a scheme based on histogram adjustment and hit-miss transform is presented to detect dim small target.In this method,histogram adjustment is adopted to enhance the signal-cluster-ratio,and hit-miss transform is used to get the suspicious targets.The experiment shows that the method is efficient in detecting dim small target with complex background.
1 citations
Journal Article•
TL;DR: In order to detect the small target in the IR grey image, a new method based on genetic algorithms(GA) to optimize the structuring element is proposed, which is simple, accurate, and adaptive.
Abstract: In this paper,in order to detect the small target in the IR grey image,a new method based on genetic algorithms(GA) to optimize the structuring element is proposedThe structuring element is very important in mathematical morphology,so that it can decide the quality of the detected small targetSince GA can find suitable approximated solutions treating the problem as a global optimization technique,the structuring element can be created and optimized by GATherefore,even if the characteristic of the detected small target is not known,the optimal structuring element can also be confirmed,and the small target can be detectedThe experiments show that this method is simple,accurate,and adaptive
1 citations