scholarly journals Analysis methods of processing images timber with defects.

2017 ◽  
Author(s):  
А.В. Илющенко
Keyword(s):  
Image Processing ◽  
Color Image ◽  
Recognition Task ◽  
Universal Method ◽  
Advantages And Disadvantages ◽  
Second Derivatives ◽  
Segmentation Methods ◽  
Segmentation Algorithms ◽  
The Impact ◽  
Selection Of

Степень точности сортировки пиломатериалов с помощью фотографического метода зависит от множества факторов: освещенности, влажности воздуха, скорости подачи пиломатериала. Влияние части факторов можно уменьшить аппаратными методами. Наибольшую сложность представляют подбор и реализация приемлемого в условиях реального производства алгоритма обработки изображения. Не менее важной задачей является правильный подбор элементов этого алгоритма (методов сегментации). В данном исследовании проведен анализ возможности применения математических и программных алгоритмов сегментации в задаче распознавания дефектов и пороков древесины. Приведена последовательность шагов по обработке изображения. Выявлены недостатки системы, взятой за основу, и внесены корректировки в нее. Выделены главные задачи сегментации: отделение чистой древесины от пороков, отделение пороков друг от друга, фильтрация шумов, выделение замкнутых границ дефектов. Проведен поиск универсального метода ее реализации. Для решения поставленной задачи в ходе исследований кратко описаны: возможность использования одной из RGB-составляющих цветного изображения, применение первой и второй производной, методы сегментации полутонового и цветного изображения, бинаризация, текстурный анализ, использование фильтров. Приведены достоинства и недостатки методов, пути решения некоторых проблем, связанных с их реализацией. Проведено испытание методов сегментации на быстродействие. Представлены результаты исследований, в том числе причины, по которым некоторые методы не применимы в условиях реального производства. Сделан вывод о том, что универсального метода для выделения всех пороков и дефектов на фоне чистой древесины среди рассмотренных выше не существует. The degree of precision sorting plants by the photographic method depends on many factors: lighting, humidity, feed rate lumber. The impact of the factors you can not reverse the program activities. The greatest difficulty is the selection and implementation of the most appropriate in terms of real output image processing circuit. No less important is the proper selection of the elements of this scheme (segmentation methods). This study was conducted to analyze the possibility of applying mathematical and software defects in segmentation algorithms recognition task and timber defects. Shows the sequence of steps for image processing. Disadvantages of the system, taken as a basis, and adjustments made to it. Identify the main problem of segmentation: separating the clean wood of vices, evils separation from each other, noise filtering, isolation defects closed borders. Is looking for a universal method of its implementation. To solve this problem in the course of research have been briefly described: the possibility of using one of the color image RGB-components, use first and second derivatives, and methods of segmentation halftone color image binarization, texture analysis, and the use of filters. Presents the advantages and disadvantages of methods, ways to solve some of the problems associated with their implementation. A test of the performance of the segmentation methods. The results of studies, including the reasons for which some of the methods are not applicable in real production. It was concluded that a universal method for the isolation of all vices and defects on the background clean timber does not exist among the above.

scholarly journals Review of Road Segmentation for SAR Images

2021 ◽  
Vol 13 (5) ◽  
pp. 1011
Author(s):  
Zengguo Sun ◽  
Hui Geng ◽  
Zheng Lu ◽  
Rafał Scherer ◽  
Marcin Woźniak
Keyword(s):  
Rapid Development ◽  
Synthetic Aperture ◽  
Practical Significance ◽  
Future Research ◽  
Sar Images ◽  
The Road ◽  
Advantages And Disadvantages ◽  
Segmentation Methods ◽  
Segmentation Algorithms ◽  
Road Segmentation

Road segmentation for synthetic aperture radar (SAR) images is of great practical significance. With the rapid development and wide application of SAR imaging technology, this problem has attracted much attention. At present, there are numerous road segmentation methods. This paper analyzes and summarizes the road segmentation methods for SAR images over the years. Firstly, the traditional road segmentation algorithms are classified according to the degree of automation and the principle. Advantages and disadvantages are introduced successively for each traditional method. Then, the popular segmentation methods based on deep learning in recent years are systematically introduced. Finally, novel deep segmentation neural networks based on the capsule paradigm and the self-attention mechanism are forecasted as future research for SAR images.

scholarly journals The Impact of Neural Network Techniques in the Optimization of the Image Processing

2020 ◽  
Vol 55 (2) ◽  
Author(s):  
Dalya Abdullah Anwer
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Medical Imaging ◽  
Threshold Value ◽  
World Health ◽  
Morphological Operations ◽  
Segmentation Methods ◽  
The World ◽  
Feature Values ◽  
The Impact

Nowadays, image processing is widely utilized in many applications and for various purposes. Scholars proposed and suggested various techniques of image processing. The neural network is one of the main processing techniques, which is a state-of-art method. This paper aims to investigate neural network techniques in the field of image processing. Moreover, medical imaging, as well as increasing trends of utilizing digital medical imaging, has gained huge attention in the health sectors. In this regard, this paper focuses on the effect of neural networks in optimizing medical image processing. In this context, the early diagnosis and detection of the eye have an important role in the avoidance of visual impairment, because of the fact that around 45 million people have visual impairments all over the world, according to the World Health Organization. For this reason, the current paper introduces a new method based on image processing for vascular segmentation based on a morphological active contour. Then, segmentation carried out based on morphological operations, fuzzy c-means, and watershed transform. The output of such segmentation methods was given to conventional neural network. The optimized feature values are then extracted. The threshold value is set to compare these optimized feature values. From this, the best segmentation methods will be obtained.

scholarly journals The Impact of Material and Design Criteria on the Assessment of Negligible Creep

2009 ◽  
Author(s):  
Robert I. Jetter ◽  
T.-L. Sam Sham ◽  
Robert W. Swindeman
Keyword(s):  
Wall Thickness ◽  
Failure Modes ◽  
Normal Operation ◽  
Regulatory Review ◽  
Advantages And Disadvantages ◽  
Asme Code ◽  
Vessel Material ◽  
The Impact ◽  
Reactor Pressure ◽  
Selection Of

Two of the proposed High Temperature Gas Reactors (HTGRs) under consideration for a demonstration plant have the design object of avoiding creep effects during normal operation. The goal of negligible creep could have different interpretations depending upon what failure modes are considered and associated criteria for avoiding the effects of creep. This paper addresses the criteria for negligible creep in Subsection NH of Section III of the ASME B&PV Code, other international design codes and some currently suggested criteria modifications and their impact on permissible operating temperatures for various reactor pressure vessel materials. There are a number of other considerations for the selection of vessel material besides avoiding creep effects. Of particular interest for this review are (1) the material’s allowable stress level and impact on wall thickness (the goal being to minimize required wall thickness) and (2) ASME Code approval (inclusion as a permitted material in the relevant Section and Subsection of interest) to expedite regulatory review and approval. The application of negligible creep criteria to two of the candidate materials, SA533 and Mod 9Cr-1Mo, and to a potential alternate, normalized and tempered 2 1/4 Cr-1Mo, are illustrated and the relative advantages and disadvantages are discussed.

The Role and Characteristics of Hybrid Approaches to Project Management in the Development of Technology-Based Products and Services

2020 ◽  
pp. 875697282095688
Author(s):  
Flávio Copola Azenha ◽  
Diane Aparecida Reis ◽  
André Leme Fleury
Keyword(s):  
Project Management ◽  
Management Practices ◽  
Service Development ◽  
Management Approach ◽  
Advantages And Disadvantages ◽  
Hybrid Approaches ◽  
Develop Technology ◽  
Multiple Case ◽  
The Impact ◽  
Selection Of

There is a trend of combining agile and traditional project management practices for technology-based product and service development in the search for more agility. Although there are, in the literature, hybrid models that propose combinations of traditional and agile approaches, there are no studies that discuss the impact of the adoption of this approach in organizations in practice. Consequently, guidance on the selection of the most appropriate project management approach has remained largely theoretical, rather than based on companies’ experiences. The objective of this research is to analyze how organizations that develop technology-based products and services apply hybrid approaches to project management, their characteristics, advantages, and disadvantages, conducting a literature review and multiple case studies as research methods. Results reveal that hybrid approaches to project management are currently fundamental for companies in order to deal with distinct organizational cultures, specific processes, customer contractual requirements, and project specificities. This study also led to a consolidated list of the characteristics of hybrid approaches to project management.

scholarly journals Research on color image segmentation

2018 ◽  
Vol 25 (03) ◽  
pp. 138-143
Author(s):  
Wang He Xi Ge Tu ◽  
Bolormaa D
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Image Segmentation ◽  
Digital Image Processing ◽  
Color Image ◽  
Color Image Segmentation ◽  
Primary Analysis ◽  
Programming Tools ◽  
Segmentation Methods ◽  
Segmentation Image

The basic foundation for the development of the image processing is image segments. Primary analysis, such as analysis of images and visualization of images, begins with segmentation. Image segmentation is one of the important parts of digital image processing. Depending on the accuracy and accuracy of the segmentation, the results of the image analysis, including the size of the object, the size of the object, and so on. In the first section of this study, briefly describe the types of image segments. Also use Mathlab language's powerful modern programming tools to explore the image segmentation methods and compare the results. As a result of the experiment, it is more accurate to accurately measure the trajectory of the image segmentation of the image as a result of the Otsu-based method of B space. This will apply to further research. Өнгөний мэдээлэлд суурилсан дүрс сегментчлэх аргын судалгаа Хураангуй: Дүрс боловсруулах судалгааны ажлын үндсэн суурь нь дүрс сегментчлэл юм. Дүрсэнд анализ хийх, дүрсийг ойлгох зэрэг анхан шатны боловсруулалт нь дүрс сегментчлэхээс эхэлдэг. Дүрс сегментчлэл нь дижитал дүрс боловсруулалтын чухал хэсгүүдийн нэг юм. Сегментчлэлийг хэр зэрэг үнэн зөв, нарийвчлал сайтай хийснээс шалтгаалан, дараагийн дүрс таних, обьектын хэмжээ зэрэг дүрс шинжлэлийн алхамын үр дүн ихээхэн хамаардаг. Энэхүү судалгааны ажлын эхний хэсэгт дүрс сегментчлэх арга төрлүүдийн талаар товч танилцуулна. Мөн орчин үеийн програмчлалын хүчтэй хэрэгсэл болох Mathlab хэлний функцуудыг ашиглан дүрс сегментчилж гарсан үр дүнгийн харьцуулалтыг танилцууллаа. Туршилтын үр дүнд RGB өнгөний орон зайн B бүрэлдэхүүнд суурилсан Otsu-ийн аргийг ашиглан дүрсийг сементчилэх нь уламжлалт дүрс сегментчилэх аргаас нэн сайн үр дүнтай илүү нарийвчлалтай байна. Үүнийг цаашдын судалгааны ажилдаа хэрэглэх болно. Түлхүүр үг: RGB дүрс, босго (Threshold) утга, гистограм, Otsu-ийн арга, дүрс боловсруулалт

scholarly journals Improving the program elements of the sawnwood sorting system

2017 ◽  
Author(s):  
А.В. Илющенко ◽  
А.Н. Чубинский
Keyword(s):  
Mathematical Model ◽  
Image Processing ◽  
Processing Algorithm ◽  
Photographic Method ◽  
Universal Method ◽  
Sampling Frame ◽  
Image Processing Algorithm ◽  
Second Derivatives ◽  
Sorting System ◽  
The Mathematical Model

Степень точности сортировки пиломатериалов с помощью фотографического метода зависит от множества факторов: освещённости, влажности воздуха, скорости подачи пиломатериала. Наибольшую сложность представляет подбор и реализация приемлемого в условиях реального производства алгоритма обработки изображения. Отсутствие универсального метода сегментации изображения для распознавания пороков и дефектов древесины поставило задачу поиска их комбинации. Определена исходная выборка изображений пиломатериалов с пороками и дефектами. На базе выборки продемонстрированы результаты обработки изображений фильтрами Собеля и Превита; фильтром, использующим текстурный анализ с применением энтропии; сегментацией на основе первой и второй производной. Сделаны выводы о том, что применение фильтрации позволило отказаться от операции подавления световой структуры и бинаризации, а также выделять текстуру древесины, применение сегментации на основе производной – выделять текстуру древесины и области пороков, применение сегментации на основе энтропии – определять зоны ворсистости. Разработана математическая модель порока древесины, позволяющая определять признаки пороков неограниченным количеством ступеней кусочной функции за счет объединения всех признаков в единый вектор. Представлена математическая модель поверхности пиломатериала, позволяющая собирать воедино сведения о всех его пластях посредством объединения матриц изображений. Выявлены недостатки алгоритма, взятого за основу, и внесены корректировки в него. Представлен алгоритм обработки изображений, включающий применение сегментации на основе первой и второй производной и применение математических моделей поверхности пиломатериала и принятия решения о его виде. The degree of precision in the sorting of sawnwood using the photographic method depends on a variety of factors: light, humidity, speed of lumber. The most difficult is to pick and implement an image-processing algorithm that is acceptable in the real manufacturing environment. The lack of a universal method for segmenting the image to recognize the flaws and defects of the wood has made the task of finding a combination of them. The original sampling of lumber with flaws and defects has been defined. The sampling frame shows the results of image processing by Sobel and presets filters, a filter using entropy-based texture analysis, first-and second-derived segmentation. It has been concluded that the use of filtering has eliminated the suppression of the light structure and binarization, as well as the texture of wood, the use of segmentation based on derivative-highlighting the texture of wood and the areas of vice, using entropy-based segmentation-define added zones. A mathematical model of wood deficiency has been developed, allowing for the identification of the symptoms of an unrestrained number of functions by combining all features into a single vector. Provides a mathematical model of the lumber surface, which allows you to collect information about all its layers by combining image matrices. The deficiencies of the algorithm taken as a basis were identified and adjustments made to it. Provides an image processing algorithm that includes the application of segmentation based on the first and second derivatives and the application of the mathematical model of the lumber surface and the decision on its appearance.

Methods for Restricting Maximum Exposure Rate in Computerized Adaptative Testing

Methodology ◽  
2007 ◽  
Vol 3 (1) ◽  
pp. 14-23 ◽  
Author(s):  
Juan Ramon Barrada ◽  
Julio Olea ◽  
Vicente Ponsoda
Keyword(s):  
Measurement Accuracy ◽  
Computerized Adaptive Testing ◽  
Computation Time ◽  
Adaptive Testing ◽  
Exposure Rate ◽  
Control Parameters ◽  
The Impact ◽  
Two Alternatives ◽  
Selection Of ◽  
Maximum Exposure

Abstract. The Sympson-Hetter (1985) method provides a means of controlling maximum exposure rate of items in Computerized Adaptive Testing. Through a series of simulations, control parameters are set that mark the probability of administration of an item on being selected. This method presents two main problems: it requires a long computation time for calculating the parameters and the maximum exposure rate is slightly above the fixed limit. Van der Linden (2003) presented two alternatives which appear to solve both of the problems. The impact of these methods in the measurement accuracy has not been tested yet. We show how these methods over-restrict the exposure of some highly discriminating items and, thus, the accuracy is decreased. It also shown that, when the desired maximum exposure rate is near the minimum possible value, these methods offer an empirical maximum exposure rate clearly above the goal. A new method, based on the initial estimation of the probability of administration and the probability of selection of the items with the restricted method ( Revuelta & Ponsoda, 1998 ), is presented in this paper. It can be used with the Sympson-Hetter method and with the two van der Linden's methods. This option, when used with Sympson-Hetter, speeds the convergence of the control parameters without decreasing the accuracy.

Estimating OLED Display Device Lifetime from pixel and screen brightness and its application

2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan
Keyword(s):  
Image Processing ◽  
Power Consumption ◽  
Model Parameters ◽  
Display Device ◽  
Image Processing Algorithm ◽  
Pixel Value ◽  
Device Lifetime ◽  
The Impact ◽  
Oled Display

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.

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