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About 2,746 papers for “Structuring element”

Structuring Element

B. S. Daya Sagar, D. Arun Kumar · Encyclopedia of earth sciences series/Encyclopedia of earth sciences · 2022

Cited by 0

Structuring Element

B. S. Daya Sagar, D. Arun Kumar · Encyclopedia of earth sciences series/Encyclopedia of earth sciences · 2023

Cited by 2

Structuring element.

Martin Georg Ljungqvist (341321), Michael Engelbrecht Nielsen (341322), Bjarne Kjær Ersbøll (341323) et al. · Figshare · 2015

Cited by 0Open access

Structuring element.

Martin Georg Ljungqvist (341321), Michael Engelbrecht Nielsen (341322), Bjarne Kjær Ersbøll (341323) et al. · Figshare · 2015

<p>Disk of radius 1–11 pixels created using a decomposition method with a neighbourhood of 4 pixels.</p>

Cited by 0Open access

Gray-scale structuring element decomposition

Octavia Camps, Tapas Kanungo, R.M. Haralick · IEEE Transactions on Image Processing · 1996

Efficient implementation of morphological operations requires the decomposition of structuring elements into the dilation of smaller structuring elements. Zhuang and Haralick (1986) presented a search algorithm to find optimal decompositions of structuring elements in binary morphology. We use the concepts of Top of a set and Umbra of a surface to extend this algorithm to find an optimal decomposition of any arbitrary gray-scale structuring element.

Cited by 17

Structuring Element for Secure Reversible Watermarking

Dao Nam Anh, Pham Quang Huy · 2020

The ability to embed data into image with reversibility would allow host image can be restored from modification in embedding task. Structuring elements provided an information-rich link of host image before and after embedding data that could be important in the development of new way of exploring secure competence. We show how a structuring element can be designed for a gray images and used in a filter to allocate positions to hide securely secret data. The pixel locations are then collected to offer capacity of hiding data for the host image. We also demonstrate a connection between the structuring elements and the capacity to keep certainly high detecting complexity.

Cited by 0

Fast morphology hardware using large‐sized structuring element

Shoji Kojima, Yoshinobu Ebisawa, T. Miyakawa · Systems and Computers in Japan · 1994

Abstract Mathematical morphology is one of the data processing methods that is extremely useful for image processing and has many applications, such as, noise elimination, shape description, texture analysis, and so on. The mathematical base of morphological processing is dilation and erosion which are described by set analysis and can be expressed in logical AND, OR notation. Localized parallel processing including morphological processing is not suitable to Neumann architecture because of the memory access bottleneck which makes it hard to achieve the high throughout data processing required in applications such as video image processing. Also the cytocomputer aimed at fast image processing has a drawback in that it can handle only very small structuring elements. In this paper, first, an algorithm is presented which accelerates morphological image processing. Next, the algorithm to design a specialized hardware which processes the real‐time video image is implemented and finally, an application of this specialized hardware for medical use is described.

Cited by 10

Optical morphological processor with a dynamically reconfigurable structuring element

Tien‐Hsin Chao · Optical Society of America Annual Meeting · 1992

An innovative optical morphological processor with dynamic reconfigurability is introduced. This processor is able to perform basic morphological operations such as the erosion or dilation in a single pass. With the use of a binary-optic diffraction grating, the structuring element (or kernel) required for these two operations can be obtained with a reconfigurable size, depending on the processing needs. A custom built 2-D output photodetector array is utilized to perform thresholding detection and to provide a feedback path to the input spatial light modulator. Image clean-up operations, including noise and clutter removal, can be obtained through iterative combination of multiple dilation and erosion operations with high speed and full programmability. Detailed system analyses as well as experimental demonstrations of various pattern recognition applications will be presented.

Cited by 0

Sequential Structuring Element for CFG Induction Using Genetic Algorithm

Nitin S. Choubey, M. U. Kharat · International Journal of Computer Applications · 2010

This paper investigates the induction of Context free Grammar with genetic algorithm. The genetic algorithm is not very effective at this To overcome this problem we investigate combined effect of two methods for structuring the chromosomes. The first is to bias the distribution of Non-terminals in the chromosome at the time of chromosome generation as well as updating. The latter approach is sequential structural mapping from chromosome to grammar. It is shown that biasing the chromosome in this fashion produces extremely fast convergence as shown in the result section. Grammars are an extremely general and useful tool with many applications. These include the higher levels of signal processing, such as pattern recognition. However, the application of grammars is limited by the algorithms we can apply to infer them from samples of data. The main contribution of this paper is the effective decoding of the context free grammar from chromosomes with the distinct approaches mentioned.

Cited by 12Open access

High precision building documentation: element definition and data structuring

Dr. Erwin Heine · 1999

In this paper a methodology of building documentation is presented which is focused on the development of a 3D GIS. The methodology is based on the description of buildings by means of hierarchically structured architectural elements. This form fulfills the requirements of spatial databases and thus enables the implementation in 3D information systems.

Cited by 0

Image denoising algorithm based on PSO optimizing structuring element

Youlian Zhu, Cheng Huang · 2012

A new image denoising algorithm is proposed to deal with information loss in the conventional morphological image denoising process. The algorithm uses median operation to improve morphological operations' performance, which called median closing operation. It gives a mathematical model of the structuring element unit (SEU) composed of a zero square matrix. The particle swarm optimization (PSO) algorithm is employed for choosing the size of structuring element. The value of peak signal to noise ratio (PSNR) is taken as a fitness function, and the transformed value of the particle's position is taken as the size of the structuring element. Experimental results show that the denoising performance of the proposed algorithm has obvious superiority than conventional morphological algorithm. It can overcome the inherent deficiency of conventional morphological operations, adaptively obtain the size of the structuring element, and effectively remove impulse noise from images, especially for the image whose signal to noise ratio value is relatively low. So it has a good prospect in image processing.

Cited by 10

An Analysis of Morphological Operation Using Arbitrary Structuring Element

A. P. Ilayaraja, M. P. Gopinath · 2014

Mathematical morphology with spatially variant structuring elements outperforms translation-invariant structuring elements in various applications. However, supporting a variable structuring element shape imposes an overwhelming computational complexity, dramatically increasing with the size of the structuring element. Dilation and erosion are often used in combination to implement image processing operations. The image content and the number of gray levels used does not influence the computing time required. The operator for each size and shape of the structuring element must be done separately, but here the filtering with multiple structuring elements is done in one operation and this reduces the computational requirements very much. The method finds applications in the areas like granulometrices, dilation-erosion scale spaces, and template matching using the hit-or-miss to transform. In this paper we are proposing about the computational performance advantage over existing methods where structuring elements are used that cannot be easily decomposed into linear structuring elements.

Cited by 0

Multi structuring element top-hat transform to detect linear features

Xiangzhi Bai, Fugen Zhou · 2010

Multi structuring element top-hat transform is proposed in this paper to improve the performance of top-hat transform. The desired image feature is treated as a set. And, the set is divided into different subsets. Then, multi structuring elements corresponding to different subsets are constructed. After that, top-hat transform is performed by using the constructed structuring elements, and the results are combined and processed to reconstruct the desired image feature. To verify the efficiency of multi structuring element top-hat transform, the application of linear feature detection is discussed. The analysis and experimental results of multi structuring element top-hat transform show that, because of the efficient performance of multi structuring element top-hat transform, the linear features of different real images in different applications can be efficiently detected. Moreover, multi structuring element top-hat transform can be widely used in different applications.

Cited by 13