Segmentation of articular cartilage and early osteoarthritis based on the fuzzy soft thresholding approach driven by modified evolutionary ABC optimization and local statistical aggregation

Articular cartilage assessment, with the aim of the cartilage loss identification, is a crucial task for the clinical practice of orthopedics. Conventional software (SW) instruments allow for just a visualization of the knee structure, without post processing, offering objective cartilage modeling. In this paper, we propose the multiregional segmentation method, having ambitions to bring a mathematical model reflecting the physiological cartilage morphological structure and spots, corresponding with the early cartilage loss, which is poorly recognizable by the naked eye from magnetic resonance imaging (MRI). The proposed segmentation model is composed from two pixel's classification parts. Firstly, the image histogram is decomposed by using a sequence of the triangular fuzzy membership functions, when their localization is driven by the modified artificial bee colony (ABC) optimization algorithm, utilizing a random sequence of considered solutions based on the real cartilage features. In the second part of the segmentation model, the original pixel's membership in a respective segmentation class may be modified by using the local statistical aggregation, taking into account the spatial relationships regarding adjacent pixels. By this way, the image noise and artefacts, which are commonly presented in the MR images, may be identified and eliminated. This fact makes the model robust and sensitive with regards to distorting signals. We analyzed the proposed model on the 2D spatial MR image records. We show different MR clinical cases for the articular cartilage segmentation, with identification of the cartilage loss. In the final part of the analysis, we compared our model performance against the selected conventional methods in application on the MR image records being corrupted by additive image noise.Web of Science117art. no. 86

Surface Defect Classification for Hot-Rolled Steel Strips by Selectively Dominant Local Binary Patterns

Developments in defect descriptors and computer vision-based algorithms for automatic optical inspection (AOI) allows for further development in image-based measurements. Defect classification is a vital part of an optical-imaging-based surface quality measuring instrument. The high-speed production rhythm of hot continuous rolling requires an ultra-rapid response to every component as well as algorithms in AOI instrument. In this paper, a simple, fast, yet robust texture descriptor, namely selectively dominant local binary patterns (SDLBPs), is proposed for defect classification. First, an intelligent searching algorithm with a quantitative thresholding mechanism is built to excavate the dominant non-uniform patterns (DNUPs). Second, two convertible schemes of pattern code mapping are developed for binary encoding of all uniform patterns and DNUPs. Third, feature extraction is carried out under SDLBP framework. Finally, an adaptive region weighting method is built for further strengthening the original nearest neighbor classifier in the feature matching stage. The extensive experiments carried out on an open texture database (Outex) and an actual surface defect database (Dragon) indicates that our proposed SDLBP yields promising performance on both classification accuracy and time efficiencyPeer reviewe

Local Defects in colloidal quantum dot thin films measured via spatially resolved multi-modal optoelectronic spectroscopy.

The morphology, chemical composition, and electronic uniformity of thin-film solution-processed optoelectronics are believed to greatly affect device performance. Although scanning probe microscopies can address variations on the micrometer scale, the field of view is still limited to well under the typical device area, as well as the size of extrinsic defects introduced during fabrication. Herein, a micrometer-resolution 2D characterization method with millimeter-scale field of view is demonstrated, which simultaneously collects photoluminescence spectra, photocurrent transients, and photovoltage transients. This high-resolution morphology mapping is used to quantify the distribution and strength of the local optoelectronic property variations in colloidal quantum dot solar cells due to film defects, physical damage, and contaminants across nearly the entire test device area, and the extent to which these variations account for overall performance losses. It is found that macroscopic defects have effects that are confined to their localized areas, rarely prove fatal for device performance, and are largely not responsible for device shunting. Moreover, quantitative analysis based on statistical partitioning methods of such data is used to show how defect identification can be automated while identifying variations in underlying properties such as mobilities and recombination strengths and the mechanisms by which they govern device behavior.DMR-1807342 - National Science Foundation; Hopkins Extreme Materials InstituteAccepted manuscrip

Generalized Completed Local Binary Patterns for Time-Efficient Steel Surface Defect Classification

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted ncomponent of this work in other works.Efficient defect classification is one of the most important preconditions to achieve online quality inspection for hot-rolled strip steels. It is extremely challenging owing to various defect appearances, large intraclass variation, ambiguous interclass distance, and unstable gray values. In this paper, a generalized completed local binary patterns (GCLBP) framework is proposed. Two variants of improved completed local binary patterns (ICLBP) and improved completed noise-invariant local-structure patterns (ICNLP) under the GCLBP framework are developed for steel surface defect classification. Different from conventional local binary patterns variants, descriptive information hidden in nonuniform patterns is innovatively excavated for the better defect representation. This paper focuses on the following aspects. First, a lightweight searching algorithm is established for exploiting the dominant nonuniform patterns (DNUPs). Second, a hybrid pattern code mapping mechanism is proposed to encode all the uniform patterns and DNUPs. Third, feature extraction is carried out under the GCLBP framework. Finally, histogram matching is efficiently accomplished by simple nearest-neighbor classifier. The classification accuracy and time efficiency are verified on a widely recognized texture database (Outex) and a real-world steel surface defect database [Northeastern University (NEU)]. The experimental results promise that the proposed method can be widely applied in online automatic optical inspection instruments for hot-rolled strip steel.Peer reviewe

Non-contact Microelectronic Device Inspection Systems And Methods

Non-contact microelectronic device inspection systems and methods are discussed and provided. Some embodiments include a method of generating a virtual reference device (or chip). This approach uses a statistics to find devices in a sample set that are most similar and then averages their time domain signals to generate the virtual reference. Signals associated with the virtual reference can then be correlated with time domain signals obtained from the packages under inspection to obtain a quality signature. Defective and non-defective devices are separated by estimating a beta distribution that fits a quality signature histogram of inspected packages and determining a cutoff threshold for an acceptable quality signature. Other aspects, features, and embodiments are also claimed and described.Georgia Tech Research Corporatio

Inspection System And Method For Bond Detection And Validation Of Surface Mount Devices Using Sensor Fusion And Active Perception

A hybrid surface mount component inspection system which includes both vision and infrared inspection techniques to determine the presence of surface mount components on a printed wiring board, and the quality of solder joints of surface mount components on printed wiring boards by using data level sensor fusion to combine data from two infrared sensors to obtain emissivity independent thermal signatures of solder joints, and using feature level sensor fusion with active perception to assemble and process inspection information from any number of sensors to determine characteristic feature sets of different defect classes to classify solder defects.Georgia Tech Research Corporatio

Product assurance technology for procuring reliable, radiation-hard, custom LSI/VLSI electronics

Advanced measurement methods using microelectronic test chips are described. These chips are intended to be used in acquiring the data needed to qualify Application Specific Integrated Circuits (ASIC's) for space use. Efforts were focused on developing the technology for obtaining custom IC's from CMOS/bulk silicon foundries. A series of test chips were developed: a parametric test strip, a fault chip, a set of reliability chips, and the CRRES (Combined Release and Radiation Effects Satellite) chip, a test circuit for monitoring space radiation effects. The technical accomplishments of the effort include: (1) development of a fault chip that contains a set of test structures used to evaluate the density of various process-induced defects; (2) development of new test structures and testing techniques for measuring gate-oxide capacitance, gate-overlap capacitance, and propagation delay; (3) development of a set of reliability chips that are used to evaluate failure mechanisms in CMOS/bulk: interconnect and contact electromigration and time-dependent dielectric breakdown; (4) development of MOSFET parameter extraction procedures for evaluating subthreshold characteristics; (5) evaluation of test chips and test strips on the second CRRES wafer run; (6) two dedicated fabrication runs for the CRRES chip flight parts; and (7) publication of two papers: one on the split-cross bridge resistor and another on asymmetrical SRAM (static random access memory) cells for single-event upset analysis

<i>In situ</i> observation of strain and phase transformation in plastically deformed 301 austenitic stainless steel

To inform the design of superior transformation-induced plasticity (TRIP) steels, it is important to understand what happens at the microstructural length scales. In this study, strain-induced martensitic transformation is studied by in situ digital image correlation (DIC) in a scanning electron microscope. Digital image correlation at submicron length scales enables mapping of transformation strains with high confidence. These are correlated with electron backscatter diffraction (EBSD) prior to and post deformation process to get a comprehensive understanding of the strain-induced transformation mechanism. The results are compared with mathematical models for enhanced prediction of strain-induced martensitic phase transformation

Mechanical Properties of Microstructural Components of Inorganic Materials

Disertační práce se zabývá studiem strukturních a mechanických vlastností anorganických materiálů. Cílem je nalezení jednotlivých fází ve zkoumaném materiálu a hlavně lokalizace (mechanicky) nejslabšího místa, jeho ovlivnění a následně výroba materiálu o lepších mechanických vlastnostech. Z důvodu velkého množství použitých metod je základní teorie vložena vždy na začátku příslušné kapitoly. Taktéž z důvodu značného množství výsledků jsou na konci kapitol uvedeny dílčí závěry. Práce je rozdělena na tři části, kdy první se zabývá seznámením s možnostmi modelování mikro-mechanických vlastností a provedením experimentů umožňujících posouzení rozsahu platnosti některého modelu. V druhé části je provedeno shrnutí současných možností indentačních zkoušek pro měření mechanických vlastností strukturních složek betonu a praktické zvládnutí metodiky vhodné k užití pro výzkum materiálů zkoumaných domovským pracovištěm. V třetí části je navržena metoda identifikace nejslabších článků struktury anorganických pojiv a její ověření na konkrétním materiálu zkoumaném na domovském pracovišti. V této dizertační práci jsou použity tyto metody: kalorimetrie, ultrazvukové testování, jednoosá pevnost v tlaku, nanoindentace, korelativní mikroskopie a rastrovací elektronová mikroskopie s energiově disperzním spektrometrem. Dílčími výsledky jsou kompletní charakterizace cementových materiálů, upřesnění stávajících poznatků a nalezení optimálního postupu pro charakterizaci. Hlavním výsledkem je inovativní přístup vedoucí k pozitivnímu ovlivnění materiálu.The doctoral thesis deals with study of structural and mechanical properties of inorganic materials. Goal is to find the weakest (mechanically) phases and interfaces of material. By affecting these structures it should be possible consequently produce a material with better mechanical properties. Due to the large amount of used methods the basic theory is discussed always in the beginning of relevant chapter. Similarly, due to the considerable amount of results every chapter includes partial conclusions. The work is divided in three parts. The first deals with the introduction of the possibilities of modeling micro-mechanical properties and performing of experiments that allow assessment of the scope of some model. In second part itis performed an overview of current possibilities of indentation tests for measuring mechanical properties of structural components of concrete and the practical managing of methods suitable for use for materials research examined at our faculty. In third part the method of identifying the weakest points in structure of inorganic binders is proposed and validation on the particular material examined at our faculty is performed. The methods used in this doctoral thesis are: calorimetry, ultrasonic testing, uniaxial compression, nanoindentation, correlative microscopy and scanning electron microscopy with energy dispersive spectrometer. Partial results are a complete characterization of cementitious materials, specification of existing knowledge and finding the optimal procedure for characterization. The main result is an innovative approach that leads to a positive effect on the material.