Wyniki wyszukiwania - BazTech

1

A discrete variable based methodology for topology optimization considering spatially uneven manufacturing errors

Xia Meng, Li Jing

Archives of Electrical Engineering

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2023

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Vol. 72, nr 4

1121--1133

EN

Manufacturing errors (MEs) are unavoidable in product fabrication. The omnipresence of manufacturing errors (MEs) in product engineering necessitates the development of robust optimization methodologies. In this research, a novel approach based on the morphological operations and interval field (MOIF) theory is proposed to address MEs in the discrete-variable-based topology optimization procedures. On the basis of a methodology for deterministic topology optimization (TO) based on the Min-Cut, MOIF introduces morphological operations to generate geometrical variations, while the dimension of the structuring element is dynamically set by the interval field function’s output. The effectiveness of the proposed approach as a powerful tool for accounting for spatially uneven ME in the TOs has been demonstrated.

2

Hybrid implementation of evolutionary algorithms in FPGAs for automatic generation of morphological image filters

Padua Bruno, Lima Denis, Fernandes Marcio, Abuassal Ali, Tempesti Gianluca, Pedrino Emerson

Przegląd Elektrotechniczny

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2020

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R. 96, nr 4

12--16

EN

This paper proposes a novel hybrid software/hardware system to automatically create ﬁlters for image processing based on genetic algorithms and mathematical morphology. Experimental results show that the hybrid system, implemented using a combination of a NIOS-II processor and a custom hardware accelerator in an Altera FPGA device, is able to generate solutions that are equivalent to the software version in terms of quality in approximately one third of the time.

PL

W artykule zaproponowano nowe hybrydowe oprogramowanie do automatycznego tworzenia ﬁltrów graﬁki bazuj ˛acych na algorytmach genetycznych i morfologii matematycznej. Eksperymenty wykazały ˙ze proponowany system wykorzystuj ˛acy procesor NIOS-II i Altera FPGA jest w stanie generowa´c rozwi ˛azanie niemal trzy razy szybciej ni˙z dotychczas stosowane systemy.

3

Aggregate segmentation of asphaltic mixes using digital image processing

Reyes-Ortiz Oscar R., Mejía M., Useche-Castelblanco J. S.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2019

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Vol. 67, nr 2

279--287

EN

The study of the different engineering materials according to their mechanical and dynamic characteristics has become an area of research interest in recent years. Several studies have verified that the mechanical properties of the material are directly affected by the distribution and size of the particles that compose it. Such is the case of asphalt mixtures. For this reason, different digital tools have been developed in order to be able to detect the structural components of the elements in a precise, clear and efficient manner. In this work, a segmentation model is developed for different types of dense-graded asphalt mixtures with grain sizes from 9.5 mm to 0.0075 mm, using sieve size reconstruction of the laboratory production curve. The laboratory curve is used to validate the particles detection model that uses morphological operations for elements separation. All this with the objective of developing a versatile tool for the analysis and study of pavement structures in a non-destructive test. The results show that the model presented in this work is able to segment elements with an area greater than 0.0324 mm2 and reproduce the sieve size curves of the mixtures with a high percentage of precision.

4

A new computer-based approach for fully automated segmentation of knee meniscus from magnetic resonance images

Saygılı A., Albayrak S.

Biocybernetics and Biomedical Engineering

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2017

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Vol. 37, no. 3

432--442

EN

Menisci are tissues that enable mobility and absorb excess loads on the knee. Problems in meniscus can trigger the disorder of osteoarthritis (OA). OA is one of the most common causes of disability, especially among young athlethes and elderly people. Therefore, the early diagnosis and treatment of abnormalities that occur in the meniscus are of significant importance. This study proposes a new computer-based and fully automated approach to support radiologists by: (i) the segmentation of medial menisci, (ii) enabling early diagnosis and treatment, and (iii) reducing the errors caused by MR intra-reader variability. In this study, 88 different MR images provided by the Osteoarthritis Initiative (OAI) are used. The histogram of oriented gradients (HOG) and local binary patterns (LBP) methods are used for feature extraction from these MR images along with the extreme learning machine (ELM) and random forests (RF) methods which are used for model learning (regression). As the first step of the pipeline, the most compact rectangular patches bounding the menisci are located. After this, meniscus boundaries are revealed by the morphological processes. Then, the similarities between these boundaries and the ground truth images are measured and compared with each other. The highest score is acquired with Dice similarity measurement with a success rate of 82%. A successful segmentation is performed on the diseased knee MR images. The proposed approach can be implemented as a decision support system for radiologists, while the segmented menisci can be used in classification of meniscal tear in future studies.

5

Wybrane metody poprawy wyników segmentacji obiektów w postaci skupisk na przykładzie obrazów kometowych

Bal A.

Pomiary Automatyka Kontrola

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2014

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R. 60, nr 5

288--289

PL

W pracy przedstawiono metody poprawy wyników segmentacji obiektów w postaci skupisk. Poprawa jakości segmentacji dla takich obiektów może być uzyskana m.in. poprzez odpowiednie połączenie filtracji dolnoprzepustowej (np. filtracji medianowej) z metodami pozwalającymi na określenie przynależności poszczególnych obszarów uzyskanych po segmentacji wybraną metodą do obszarów wynikowych reprezentujących obiekty interesujące z punktu widzenia celu segmentacji (w pracy zastosowano w tym celu operację morfologicznego zamknięcia oraz metodę grafową wykorzystującą koncepcję minimalnego drzewa rozpinającego). W pracy zwrócono także uwagę na możliwość poprawy wyników segmentacji poprzez wyznaczenie otoczki wypukłej rozpiętej na obszarach spełniających określone wymagania. Wyniki działania opisanych metod przedstawiono na przykładzie poprawy wyników segmentacji obrazów otrzymanych w wyniku jednokomórkowej elektroforezy żelowej.

EN

This paper deals with the problem of segmentation of cluster-structured objects, that is the objects which are formed by a set of unconnected elements smaller than the object. Images representing such objects are very difficult for segmentation. A good example of cluster-structured objects are “comet” images from Single Cell Gel Electrophoresis (comet assay). In the analysis of comet assay images a pivotal role plays the detection of comet regions - the comet region is formed by unconnected fragments of DNA (Fig. 1) which originate from the same cell nucleus. Because those regions are not solid, the usage of standard segmentation methods leads to poor results (Fig. 2). Pre- and post-processing methods can be used for improvement of segmentation results. Some of them are presented in the paper. The aim of the work was not the selection of the best improvement method of the comet assay segmentation results but the presentation of different approaches which could be used in the case of segmentation of this kind of objects. The first presented method is based on the idea of artificial removing of connectivity lack - this is done by the usage of a low-pass filter with large window before segmentation (Fig. 3). The next method uses the morphological closing for assignment of regions ri to the metaregion Rk which represent one comet (Fig. 4). For improving Rk shape the idea of convex hull spanned on ri ∈ Rk is used (Fig. 5). In this method the assignment condition is enclosed in structuring elements - because of limitations of the discrete space, in which the structuring element is defined, there are also some limitations of conditions which can be used. This drawback does not exist in the last of the presented method which uses the conception of the minimum spanning tree for assignment of regions ri to Rk. In this method the segmentation result is represented by graph G, whose vertexes vi represent regions ri, and length dij of edge eij between vertexes vi, and vj is equal to the closest distance between pixels of ri and rj (distances dij in general case can be variously defined). In G the minimum spanning trees Tk are searched, such that ∀eij ∈ Tk : dij ≤ ε, then for each Tk its convex hull is created - it defines the region of comet Kp (Fig. 6).

6

Neural networks for medical image processing

Pieciak T., Jaworek J., Gorgon M.

Bio-Algorithms and Med-Systems

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2011

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Vol. 7, no. 4

101--110

EN

The proposed article presents the most common types of artificial neural networks used to be performed in the field of medical imaging. The first section describes the use of artificial neural networks in the preprocessing stage, restoration of noisy and distorted images and in conjunction with morphological operations. The second part presents the artificial neural networks in image segmentation problem, particularly in adaptive binarization threshold level selection and as a complement to the active contour method.

7

Local detection of defects from image sequences

Rafajłowicz E., Wnuk M., Rafajłowicz W.

International Journal of Applied Mathematics and Computer Science

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2008

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Vol. 18, no 4

581-592

EN

Our aim is to discuss three approaches to the detection of defects in continuous production processes, which are based on local methods of processing image sequences. These approaches are motivated by and applicable to images of hot metals or other surfaces, which are uniform at a macroscopic level, when defects are not present. The first of them is based on the estimation of fractal dimensions of image cross-sections. The second and third approaches are compositions of known techniques, which are selected and tuned to our goal. We discuss their advantages and disadvantages, since they provide different information on defects. The results of their testing on 12 industrial images are also summarized.

8

Detection and segmentation of moving vehicles and trains using Gaussian mixtures, shadow detection and morphological processing

Dalka P.

Machine Graphics and Vision

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2006

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Vol. 15, No. 3/4

339-348

EN

The solution presented in this paper combines background modelling, shadow detection and morphological and temporal processing into a single system responsible for detection and segmentation of moving objects recorded with a static camera. Vehicles and trains are detected based on their pixel-level difference with respect to a continually updated background model, using a Gaussian mixture calculated separately for every pixel. The shadow detection method utilizes a colour model which allows for estimating chromatic and brightness differences between the pixel colour and the background model. Morphological and temporal operations performed on binary images denoting moving objects include connecting the components, closing and temporal filtering. Experiments carried out involve employing implemented algorithms to detect vehicles and trains in video sequences. The results achieved are described and illustrated in figures.

9

Morphological operations with subpixel resolution on digital images

Reinoso O., Sebastian J. M., Aracil R., Torres F.

Machine Graphics and Vision

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2001

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Vol. 10, No. 1

89-102

EN

In many defect inspection systems computer vision pattern matching techniques are applied. These techniques require the use of different morphological operations. In many situations, pattern images generated by classical morphological operations do not allow to detect defects in images. Small defects of pixel size can also be left unnoticed when using such pattern images. The purpose of this paper is to combine classical morphological operations with a linear interpolation process on digital images to generate these pattern images. It is possible to employ structuring elements of any size to carry out morphological operations on continuous signals. However, on gigital images or discrete signals, the size of the structuring element should be greater than pixel size. The approach described in this paper applies classical morphological operations on reconstructed images at subpixel level to generate [pattern images. In such circumstances, we can compare this procedure with the effect produced by the use of structuring elements smaller than pixel size.