Relevant bibliographies by topics / Inspection computation

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Inspection computation'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Inspection computation"

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Rau, Hsin, Kuo Hua Cho, and Yi Hsiang Wang. "Optimal Inspection Allocation for Workstations of Attribute Data with Multi-Characteristics in Multi-Station Systems." Key Engineering Materials 450 (November 2010): 397–400. http://dx.doi.org/10.4028/www.scientific.net/kem.450.397.

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. The study models multi-characteristics inspection for inspection allocation problems with workstations of attribute data in serial production systems. Either 100% or 0% inspection is performed and Type I and Type II errors are considered. In addition, this study considers three possibilities of treatment of detected nonconforming units, namely, repair, rework and scrap. With the above considerations, a profit model is developed for optimally allocating inspections. Moreover, a genetic algorithm is used to solve the problem and it is proved to have much less computation time, compared with an optimization method based on complete enumeration, especially when number of workstations and characteristics becomes more.
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Zou, Guang, Kian Banisoleiman, and Arturo González. "Bayesian maintenance decision optimisation based on computing the information value from condition inspections." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 235, no. 4 (March 26, 2021): 545–55. http://dx.doi.org/10.1177/1748006x20978127.

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A challenge in marine and offshore engineering is structural integrity management (SIM) of assets such as ships, offshore structures, mooring systems, etc. Due to harsh marine environments, fatigue cracking and corrosion present persistent threats to structural integrity. SIM for such assets is complicated because of a very large number of rewelded plates and joints, for which condition inspections and maintenance are difficult and expensive tasks. Marine SIM needs to take into account uncertainty in material properties, loading characteristics, fatigue models, detection capacities of inspection methods, etc. Optimising inspection and maintenance strategies under uncertainty is therefore vital for effective SIM and cost reductions. This paper proposes a value of information (VoI) computation and Bayesian decision optimisation (BDO) approach to optimal maintenance planning of typical fatigue-prone structural systems under uncertainty. It is shown that the approach can yield optimal maintenance strategies reliably in various maintenance decision making problems or contexts, which are characterized by different cost ratios. It is also shown that there are decision making contexts where inspection information doesn’t add value, and condition based maintenance (CBM) is not cost-effective. The CBM strategy is optimal only in the decision making contexts where VoI > 0. The proposed approach overcomes the limitation of CBM strategy and highlights the importance of VoI computation (to confirm VoI > 0) before adopting inspections and CBM.
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Huang, Yibin, Congying Qiu, Xiaonan Wang, Shijun Wang, and Kui Yuan. "A Compact Convolutional Neural Network for Surface Defect Inspection." Sensors 20, no. 7 (April 1, 2020): 1974. http://dx.doi.org/10.3390/s20071974.

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The advent of convolutional neural networks (CNNs) has accelerated the progress of computer vision from many aspects. However, the majority of the existing CNNs heavily rely on expensive GPUs (graphics processing units). to support large computations. Therefore, CNNs have not been widely used to inspect surface defects in the manufacturing field yet. In this paper, we develop a compact CNN-based model that not only achieves high performance on tiny defect inspection but can be run on low-frequency CPUs (central processing units). Our model consists of a light-weight (LW) bottleneck and a decoder. By a pyramid of lightweight kernels, the LW bottleneck provides rich features with less computational cost. The decoder is also built in a lightweight way, which consists of an atrous spatial pyramid pooling (ASPP) and depthwise separable convolution layers. These lightweight designs reduce the redundant weights and computation greatly. We train our models on groups of surface datasets. The model can successfully classify/segment surface defects with an Intel i3-4010U CPU within 30 ms. Our model obtains similar accuracy with MobileNetV2 while only has less than its 1/3 FLOPs (floating-point operations per second) and 1/8 weights. Our experiments indicate CNNs can be compact and hardware-friendly for future applications in the automated surface inspection (ASI).
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Pfingstl, Simon, Martin Steiner, Olaf Tusch, and Markus Zimmermann. "Crack Detection Zones: Computation and Validation." Sensors 20, no. 9 (April 30, 2020): 2568. http://dx.doi.org/10.3390/s20092568.

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During the development of aerospace structures, typically many fatigue tests are conducted. During these tests, much effort is put into inspections in order to detect the onset of failure before complete failure. Strain sensor data may be used to reduce inspection effort. For this, a sufficient number of sensors need to be positioned appropriately to collect the relevant data. In order to minimize cost and effort associated with sensor positioning, the method proposed here aims at minimizing the number of necessary strain sensors while positioning them such that fatigue-induced damage can still be detected before complete failure. A suitable detection criterion is established as the relative change of strain amplitudes under cyclic loading. Then, the space of all possible crack lengths is explored. The regions where the detection criterion is satisfied before complete failure occurs are assembled into so-called detection zones. One sensor in this zone is sufficient to detect criticality. The applicability of the approach is demonstrated on a representative airplane structure that resembles a lower wing section. The method shows that four fatigue critical spots can be monitored using only one strain sensor in a non-intuitive position. Furthermore, we discuss two different strain measures for crack detection. The results of this paper can be used for reliable structural health monitoring using a minimum number of sensors.
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Pathmakumar, Thejus, Vinu Sivanantham, Saurav Ghante Anantha Padmanabha, Mohan Rajesh Elara, and Thein Than Tun. "Towards an Optimal Footprint Based Area Coverage Strategy for a False-Ceiling Inspection Robot." Sensors 21, no. 15 (July 30, 2021): 5168. http://dx.doi.org/10.3390/s21155168.

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False-ceiling inspection is a critical factor in pest-control management within a built infrastructure. Conventionally, the false-ceiling inspection is done manually, which is time-consuming and unsafe. A lightweight robot is considered a good solution for automated false-ceiling inspection. However, due to the constraints imposed by less load carrying capacity and brittleness of false ceilings, the inspection robots cannot rely upon heavy batteries, sensors, and computation payloads for enhancing task performance. Hence, the strategy for inspection has to ensure efficiency and best performance. This work presents an optimal functional footprint approach for the robot to maximize the efficiency of an inspection task. With a conventional footprint approach in path planning, complete coverage inspection may become inefficient. In this work, the camera installation parameters are considered as the footprint defining parameters for the false ceiling inspection. An evolutionary algorithm-based multi-objective optimization framework is utilized to derive the optimal robot footprint by minimizing the area missed and path-length taken for the inspection task. The effectiveness of the proposed approach is analyzed using numerical simulations. The results are validated on an in-house developed false-ceiling inspection robot—Raptor—by experiment trials on a false-ceiling test-bed.
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SÖDERGÅRD, CAJ, RAIMO LAUNONEN, and JUUSO ÄIKÄS. "INSPECTION OF COLOUR PRINTING QUALITY." International Journal of Pattern Recognition and Artificial Intelligence 10, no. 02 (March 1996): 115–28. http://dx.doi.org/10.1142/s0218001496000104.

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The use of machine vision technology is being investigated at VTT for improving the colour quality and productivity of web offset printing. The visual inspection of colour quality is performed by a colour CCD camera which traverses the moving web under a stroboscopic light. The measuring locations and goal values for the colour register, the ink density and the grey balance are automatically determined from the PostScript™ description of the digital page. A set of criteria is used to find the most suitable spots for the measurements. In addition to providing data for on-line control, the page analysis estimates the zone wise link consumption of the printing plates as a basis for presetting the ink feed. Target calorimetric CIE-values for grey balance and critical colours are determined from the image originals. The on-line measurement results and their derivations from the target values are displayed in an integrated manner. The paper gives test results of computation times, measurements of register error with and without test targets and the colour measuring capabilities of the system. The results show that machine vision can be used for on-line inspection of colour print quality. This makes it possible to upgrade older printing presses to produce a colour quality that is competitive with more modern presses.
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Li, Guoyi, Chao Feng, Addishiwot Woldesenbet, Bruce King, Hamid Hadavi, Vikasini Moku, Kurt Loken, and Gary Kunkel. "Deep Learning based Optical Inspection with Centralized Analysis for High Volume Smart Manufacturing." Annual Conference of the PHM Society 12, no. 1 (November 3, 2020): 9. http://dx.doi.org/10.36001/phmconf.2020.v12i1.1282.

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Increased capabilities in data storage and exploration provide significant insights for quality assurance in a high volume manufacturing environment. However, these opportunities are associated with great challenges in analytical model development, application deployment, system throughput and reliability. While no commercial software system fully meets the needs of recording head factories in Seagate, a novel strategy named optical inspection with centralized analysis has been developed to detect defects of trailing edges of the recording heads of hard disk drives, and fail the parts when necessary. Leveraging the state-of-the-art artificial intelligence technologies, a deep learning based semantic segmentation engine is built using convolutional neural networks for optical inspection. It has shown an improved accuracy to that of visual inspection performed by human. Meanwhile, a high performance computation engine has been built as a Kubernetes cluster with multiple GPU and CPU units. It is able to achieve the target throughput of three million high-resolution images in each day (i.e., 12 TB image data and 35 images per second). With the high fidelity offered by Kubernetes cluster, the developed applications (inference engine, preprocessor, postprocessor, etc.) serve as containerized microservices independently. Such an architecture ensures the vertical and horizontal scalabilities according to the computation of each individual deployment, while all deployments communicate through an Advanced Message Queuing Protocol cluster without human interference. This analytic framework enables Industry 4.0 recording head manufacturing by integrating advanced AI technologies with a robust edge computation architecture.
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Lin, Chaochao, and Matteo Pozzi. "Optimal adaptive inspection and maintenance for redundant systems." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 235, no. 4 (May 26, 2021): 568–79. http://dx.doi.org/10.1177/1748006x211020151.

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Optimal exploration of engineering systems can be guided by the principle of Value of Information (VoI), which accounts for the topological important of components, their reliability and the management costs. For series systems, in most cases higher inspection priority should be given to unreliable components. For redundant systems such as parallel systems, analysis of one-shot decision problems shows that higher inspection priority should be given to more reliable components. This paper investigates the optimal exploration of redundant systems in long-term decision making with sequential inspection and repairing. When the expected, cumulated, discounted cost is considered, it may become more efficient to give higher inspection priority to less reliable components, in order to preserve system redundancy. To investigate this problem, we develop a Partially Observable Markov Decision Process (POMDP) framework for sequential inspection and maintenance of redundant systems, where the VoI analysis is embedded in the optimal selection of exploratory actions. We investigate the use of alternative approximate POMDP solvers for parallel and more general systems, compare their computation complexities and performance, and show how the inspection priorities depend on the economic discount factor, the degradation rate, the inspection precision, and the repair cost.
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Li, Xiong Bing, Hong Wei Hu, Ling Li, and Lin Jin Tong. "Data Compression in Automatic Ultrasonic Inspection Based on Lifting Scheme." Applied Mechanics and Materials 48-49 (February 2011): 353–56. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.353.

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In this paper, the method of data compression in ultrasonic automatic inspection using integral wavelet transform is proposed. The compression method presented is performed through signal decomposition, thresholding of wavelet transform coefficients, signal reconstruction, evaluating and optimizing algorithm performance by parameters index . The experiments show that the method has the advantages of low computation complexity， fast compression rate， high compression ratio and small reconstruction difference when it is applied to A-Wave data compression.
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HARIKRISHNAN, K. P., G. AMBIKA, and R. MISRA. "AN ALGORITHMIC COMPUTATION OF CORRELATION DIMENSION FROM TIME SERIES." Modern Physics Letters B 21, no. 02n03 (January 30, 2007): 129–38. http://dx.doi.org/10.1142/s0217984907012517.

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We present an algorithmic scheme to compute the correlation dimension D2 of a time series, without requiring the visual inspection of the scaling region in the correlation sum. It is based on the standard Grassberger–Proccacia [GP] algorithm for computing D2. The scheme is tested using synthetic data sets from several standard chaotic systems as well as by adding noise to low-dimensional chaotic data. We show that the scheme is efficient with a few thousand data points and is most suitable when a nonsubjective comparison of D2 values of two time series is required, such as, in hypothesis testing.
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Dissertations / Theses on the topic "Inspection computation"

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Zhang, Meng. "Evolutionary Learning of Boosted Features for Visual Inspection Automation." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/7324.

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Feature extraction is one of the major challenges in object recognition. Features that are extracted from one type of objects cannot always be used directly for a different type of objects, therefore limiting the performance of feature extraction. Having an automatic feature learning algorithm could be a big advantage for an object recognition algorithm. This research first introduces several improvements on a fully automatic feature construction method called Evolution COnstructed Feature (ECO-Feature). These improvements are developed to construct more robust features and make the training process more efficient than the original version. The main weakness of the original ECO-Feature algorithm is that it is designed only for binary classification and cannot be directly applied to multi-class cases. We also observe that the recognition performance depends heavily on the size of the feature pool from which features can be selected and the ability of selecting the best features. For these reasons, we have developed an enhanced evolutionary learning method for multi-class object classification to address these challenges. Our method is called Evolutionary Learning of Boosted Features (ECO-Boost). ECO-Boost method is an efficient evolutionary learning algorithm developed to automatically construct highly discriminative image features from the training image for multi-class image classification. This unique method constructs image features that are often overlooked by humans, and is robust to minor image distortion and geometric transformations. We evaluate this algorithm with a few visual inspection datasets including specialty crops, fruits and road surface conditions. Results from extensive experiments confirm that ECO-Boost performs closely comparable to other methods and achieves a good balance between accuracy and simplicity for real-time multi-class object classification applications. It is a hardware-friendly algorithm that can be optimized for hardware implementation in an FPGA for real-time embedded visual inspection applications.
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Vokál, Miroslav. "Manipulátor pro manipulaci s velkonábalem." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2014. http://www.nusl.cz/ntk/nusl-231470.

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This work deals with the construction of a specific device for handling batching, such as paper rolls wound on a paper tube. It is included in the structural design of the device, control engineering calculations nodes developed basic drawing documentation manipulator.
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Bergström, Per. "Computational methods for on-line shape inspection /." Luleå : Department of Mathematics, Luleå University of Technology, 2009. http://pure.ltu.se/ws/fbspretrieve/2505373.

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Bergström, Per. "Computational methods for on-line shape inspection." Licentiate thesis, Luleå tekniska universitet, Matematiska vetenskaper, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-18018.

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This licentiate thesis describes computational methods that solve problems occurring in industrial on-line shape quality inspection of produced items. These items are measured and compared with their corresponding CAD object. The meaning of on-line is that the inspection is done on-line in the production line, i.e. the items are not removed from the line. In practice this means that the inspection must be done very fast, both the measurement and the data analysis. The measurement is done using an optical non-contact method based on projection of fringes.The presented methods are mainly based on finding a transformation, a rotation and a translation, of the measurement values which consists of a point cloud representing the measured surface. This transformation is calculated using the iterative closest point (ICP) method such that the point cloud fits the corresponding surface of the CAD object properly. The method for finding this transformation is adapted for reiterated use, i.e. it makes use of the fact that the same CAD object is used several times for different measurements. A search tree making it possible to do this fast is proposed.When dealing with real measurements obtained from optical methods undesired measurement errors will occur, caused by reflections, dirt on lenses or other likely matters in the industrial environment. The iteratively re-weighted least squares (IRLS) method for different robust functions are used in combination with ICP for handling these errors, in order to do a correct surface matching. This result in much higher matching accuracy and almost no additional computations are needed.
Denna licentiatuppsats beskriver beräkningsmetoder för problem som uppkommer på det löpande bandet ute i tillverkningsindustrin för kvalitets kontroll av formen på producerade artiklar. Dessa artiklar är uppmätta och jämförda med dess tillhörande CAD-objekt. Att kontrollen görs online medför att den måste gå snabbt att utföra, både uppmätningen och tillhörande dataanalys. Uppmätningen görs genom att använda optiska beröringsfria mätmetoder.De presenterade metoderna baseras i huvudsak på att hitta en transformation, en rotation och en translation, av de uppmätta värdena som besår av ett punktmoln representerande den uppmätta ytan. Denna transformation beräknas genom att använda "the iterative closest point (ICP)" metoden för att passa in punktmolnet till CAD-objektet på ett lämpligt sätt. Metoden för att hitta transformationen är anpassad för upprepad användning, d.v.s. den använder det faktum att samma CAD-objekt används flera gånger för olika mätningar. En trädstruktur som möjliggör att transformationen kan beräknas snabbt är föreslagen.När mätvärden från mätningar med optiska beröringsfria metoder används uppkommer mätfel. Dessa mätfel beror på reflektioner, smuts på linser eller andra troliga omständigheter i den industriella miljön. Metoden "iteratively re-weighted least squares (IRLS) method" med olika robusta funktioner används i kombination med ICP metoden för att hantera dessa mätfel. Allt detta för att kunna passa in punktmolnet till CAD-objektet utan att mätfelen skall ha så stor inverkan. Denna metod resulterar i mycket större noggrannhet jämfört med om mätfelen inte skulle behandlas, i princip utan att för den skull behöva göra fler beräkningar.
Godkänd; 2009; 20090120 (berper); LICENTIATSEMINARIUM Ämnesområde: Teknisk-vetenskapliga beräkningar Examinator: Docent Inge Söderkvist, Luleå tekniska universitet Tid: Torsdag den 26 februari 2009 kl 10.15 Plats: A 2526, Luleå tekniska universitet
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Brierley, Nicholas. "The computational enhancement of automated non-destructive inspection." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/24736.

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In industrial NDE it is increasingly common for data acquisition to be automated, driving a recent substantial increase in the availability of data. The collected data need to be analysed and currently this is largely done manually by a skilled operator - a rather painstaking task given how rarely defects occur. Moreover, in automated NDE a region of an inspected component is typically interrogated several times, be it within a single data channel due to multiple probe passes, across several channels acquired simultaneously or over the course of repeated inspections. The systematic combination of these diverse readings is recognised to offer an opportunity to improve the reliability of the inspection, for example by enabling noise suppression, but is not achievable in a manual analysis. Hence there is scope for the inspection reliability to be improved whilst reducing the time taken for the data analysis by computational means. This thesis describes the development of a software framework providing a partial automation capability, aligning then fusing the available experimental data to declare regions of the component defect-free to a very high probability whilst readily identifying indications, thereby optimising the use of the operator's time. The framework is designed to be applicable to a wide range of automated NDE scenarios, but the focus in development has been on two distinct, industrial inspections: the ultrasonic inspection of power station turbine rotor bores and the ultrasonic immersion inspection of aerospace turbine disks. Results obtained for industrial datasets from these two applications convincingly demonstrate the benefits of using the developed software system.
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Deng, Fuqin, and 鄧輔秦. "Computational surface profilometry and its applications in semiconductor inspection." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206340.

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Non-contact surface profilometry techniques, especially the phase-measuring profilometry, have been evolved dramatically over recent years. Besides the simple triangulation configuration with a fringe pattern projection system and digital imaging system, efficient computational surface profilometry techniques have also drawn tremendous attention from both academia and a wide range of applications. In the semiconductor industry, high-precision and high-speed, automated optical inspection systems are urgently needed to ensure high quality of semiconductor devices and yield improvement on the production and assembly line. However, by assuming the measured object to be stationary, conventional approaches are not suitable for surface profilometry of moving objects. Moreover, different sources of error such as the low contrast fringe patterns on the measured object, the unevenness in the illumination and the perspective projection effect from the optics will decrease the performance of surface profilometry. To meet these challenges, we have built fringe pattern projection prototypes with projector and camera arrays for surface profilometry of moving objects along the conveyor belt. This design helps to enlarge the field of view with parallel processing. In addition, we have presented an optimization framework to investigate the sources of the error for surface profilometry and generalize various computational surface profilometry approaches under different scenarios. Under this framework, first, we investigate two important factors determining the precision of surface profilometry, namely, the condition number of the phaseshift matrix and the fringe contrast within the images of the projected fringe patterns. Then, a regularized phase-shift algorithm has been proposed to improve the reconstruction results at the low contrast regions such as on the substrate of the semiconductor devices. Second, we study the intensity fluctuation caused by the uneven illumination for surface profilometry of moving objects. After that, an illumination-reflectivity-focus model has been suggested to describe the unevenness and an illumination-invariant phase-shift algorithm has been developed to handle this uneven illumination effect. Third, the perspective projection effect from the optics also affects the accurate phase-shift estimation for a moving object. Therefore, we propose a general polynomial phase-measuring profilometry model to establish the relationship between the phase-shift and height variation for each measured point. Accordingly, a polynomial phase-shift algorithm with error compensation technique has been put forward to improve the performance of the surface profilometry for moving objects. Both simulation and real experiments from the prototype have been conducted to verify the improvement on the performance of the proposed methodologies. Furthermore, these research results have demonstrated the effectiveness and efficiency of the presented optimization framework for investigating the sources of error for surface profilometry. Moreover, the proposed computational surface profilometry techniques and the corresponding fringe pattern projection systems have been used in automated optical inspection systems for yield improvement on the production line in the semiconductor industry.
published_or_final_version
Electrical and Electronic Engineering
Doctoral
Doctor of Philosophy
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Winkvist, Stefan. "Low computational SLAM for an autonomous indoor aerial inspection vehicle." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/59055/.

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The past decade has seen an increase in the capability of small scale Unmanned Aerial Vehicle (UAV) systems, made possible through technological advancements in battery, computing and sensor miniaturisation technology. This has opened a new and rapidly growing branch of robotic research and has sparked the imagination of industry leading to new UAV based services, from the inspection of power-lines to remote police surveillance. Miniaturisation of UAVs have also made them small enough to be practically flown indoors. For example, the inspection of elevated areas in hazardous or damaged structures where the use of conventional ground-based robots are unsuitable. Sellafield Ltd, a nuclear reprocessing facility in the U.K. has many buildings that require frequent safety inspections. UAV inspections eliminate the current risk to personnel of radiation exposure and other hazards in tall structures where scaffolding or hoists are required. This project focused on the development of a UAV for the novel application of semi-autonomously navigating and inspecting these structures without the need for personnel to enter the building. Development exposed a significant gap in knowledge concerning indoor localisation, specifically Simultaneous Localisation and Mapping (SLAM) for use on-board UAVs. To lower the on-board processing requirements of SLAM, other UAV research groups have employed techniques such as off-board processing, reduced dimensionality or prior knowledge of the structure, techniques not suitable to this application given the unknown nature of the structures and the risk of radio-shadows. In this thesis a novel localisation algorithm, which enables real-time and threedimensional SLAM running solely on-board a computationally constrained UAV in heavily cluttered and unknown environments is proposed. The algorithm, based on the Iterative Closest Point (ICP) method utilising approximate nearest neighbour searches and point-cloud decimation to reduce the processing requirements has successfully been tested in environments similar to that specified by Sellafield Ltd.
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Morgan, Luke N. C. "The development of SQUID-based NDE through experimentation and computational modelling." Thesis, University of Strathclyde, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366527.

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Baldrich, i. Caselles Ramon. "Perceptual approach to a computational colour texture representation for surface inspection." Doctoral thesis, Universitat Autònoma de Barcelona, 2001. http://hdl.handle.net/10803/3022.

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El principal objectiu d'aquest treball de tesi és tractar el problema de la representació de la textura en color des del punt de vista de la visió per computador. L'extensió dels mètodes classics de processament de textura per imatges en nivells de grisos als canals d'una imatge color no assegura resultats semblants als de la percepció humana en aquesta tasca. Els mecanismes d'inducció cromàtica del sistema visual humà, estudiats en psicofísica, són fonamentals en la dependència que crea l'entorn en la percepció del color. La inducció cromàtica inclou dos efectes complementaris: l'assimilació i el contrast cromàtic. Mentre el primer ja ha estat mesurat des de la psicofísica i extés a la visió per computador, molts aspectes del segon encara queden per fer. La contribució principal d'aquesta tesi és la definició d'un operador computacional que simula el fenòmen del contrast cromàtic i que té un comportament coherent amb el del sistema visual humà en diferents problemes de la percepcció de la textura en color, ja que permet enfatitzar les diferències de color en distribucions que són quasibé unimodals i així millorar la segmentació de les regions de color. El problema que encara queda obert és la realització de mesures psicofísiques pels paràmetres de l'operador, tal com es va fer amb l's-cielab per al procés d'assimilació.
La definició de representacions computacionals de textura i color perceptuals és un objectiu de gran importància en els problemes d'inspecció automàtica de superfícies en els que els dispositius de la colorimetria clàssica no permeten donar bones mesures d'aparença de color. La segona contribució de la tesi defineix una representació computacional basada en mesures globals de color incloent-hi l'assimilació de color i mesures locals de les propietats de les regions segmentades considerant el contrast cromàtic. Aquesta representació és aplicada a la classificació de gres porcelànic.
Tenint en compte que s'han de realitzar mesures molt acurades de petites diferències, s'ha dedicat una part d'aquest treball a l'adquisició d'imatges en color, i en concret a aconseguir bones propietats de constància de color. En aquest sentit, la darrera contribució de la tesi és la definició d'un algorisme de contància de color en línea per a una càmera lineal d'alta precisió de color. Aquest mètode s'ha basat en el model lineal diagonal de constància de color prèviament garantit amb una transformació que canvia les propietats de la sensibilitat de la càmera.
The main goal of this thesis is to deal with the colour texture representation problem from a computer vision point of view. It is easy to demonstrate that the extension of classical grey level methods for texture processing to the three channels of the corresponding colour texture does not succeed in having a human-like behaviour on this visual task. Chromatic induction mechanisms of the human visual system, which have been widely studied in psychophysics, play an important role on the dependency of the colour perception from its surround. Chromatic induction includes two complementary effects: chromatic assimilation and chromatic contrast. While the former has been psychophysically measured and lately extended to computer vision, some aspects on the last one still remain to be measured. The main contribution of this thesis is a computational operator that simulates the contrast induction phenomena that has demonstrated a coherent behaviour on different texture colour perception problems, since it allows to emphasise colour differences on almost-unimodal colour distributions and consequently improving the segmentation of colour regions. An open problem that will remain open from this work is the psychophysical measurement of the operator parameters, in the same sense as it was done with the s-cielab for the assimilation process.
A perceptually consistent colour texture computational representation is a goal of extreme importance in automatic colour-textured surface inspection problems, where the classic colorimetric tools does not succeed in given good colour appearance measurements. In this scope, a second contribution is a colour-texture representation based on global colour features considering colour assimilation and local features based on properties of colour blobs considering colour contrast. This representation is applied to an automatic tile classification problem.
Since an important accuracy is needed to measure such small differences, we have devoted a great part of this work to the colour acquisition issue, and to the problem of achieving good colour constancy properties on the acquired images. In this sense, a last contribution of this work has been to define an on-line colour constancy algorithm for a high colour precision scan line camera based on a diagonal linear colour constancy model previously guaranteed by linear transform changing the camera sensitivity properties.
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White, Joseph R. "PARIS: A PArallel RSA-prime InSpection tool." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/1003.

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Modern-day computer security relies heavily on cryptography as a means to protect the data that we have become increasingly reliant on. As the Internet becomes more ubiquitous, methods of security must be better than ever. Validation tools can be leveraged to help increase our confidence and accountability for methods we employ to secure our systems. Security validation, however, can be difficult and time-consuming. As our computational ability increases, calculations that were once considered “hard” due to length of computation, can now be done in minutes. We are constantly increasing the size of our keys and attempting to make computations harder to protect our information. This increase in “cracking” difficulty often has the unfortunate side-effect of making validation equally as difficult. We can leverage massive-parallelism and the computational power that is granted by today’s commodity hardware such as GPUs to make checks that would otherwise be impossible to perform, attainable. Our work presents a practical tool for validating RSA keys for poor prime numbers: a fundamental problem that has led to significant security holes, despite the RSA algorithm’s mathematical soundness. Our tool, PARIS, leverages NVIDIA’s CUDA framework to perform a complete set of greatest common divisor calculations between all keys in a provided set. Our implementation offers a 27.5 times speedup using a GTX 480 and 33.9 times speedup using a Tesla K20Xm: both compared to a reference sequential implementation for sets of less than 200000 keys. This level of speedup brings this validation into the realm of practicality due to decreased runtime.
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Book chapters on the topic "Inspection computation"

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Iwano, Kazuo, Prabhakar Raghavan, and Hisao Tamaki. "The traveling cameraman problem, with applications to automatic optical inspection." In Algorithms and Computation, 29–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58325-4_163.

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Chen, Jinzhuo, and Tao Hong. "Application of Two-Stage Sampling in Sampling Inspection." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery, 1152–59. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70665-4_125.

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Galos, Peter, Peter Nordin, Joel Olsén, and Kristofer Sundén Ringnér. "A General Approach to Automatic Programming Using Occam’s Razor, Compression, and Self-Inspection." In Genetic and Evolutionary Computation — GECCO 2003, 1806–7. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45110-2_74.

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Martorell, Agustín, and Emilia Gómez. "Two-Dimensional Visual Inspection of Pitch-Space, Many Time-Scales and Tonal Uncertainty over Time." In Mathematics and Computation in Music, 140–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21590-2_11.

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de Trémiolles, Ghislain, Pascal Tannhof, Brendan Plougonven, Claude Demarigny, and Kurosh Madani. "Visual probe mark inspection, using hardware implementation of artificial neural networks, in VLSI production." In Biological and Artificial Computation: From Neuroscience to Technology, 1374–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0032598.

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Martín, D., M. Rincón, M. C. García-Alegre, and D. Guinea. "ARDIS: Knowledge-Based Dynamic Architecture for Real-Time Surface Visual Inspection." In Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira’s Scientific Legacy, 395–404. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02264-7_41.

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Rosandich, Ryan G. "Computational approach to artificial vision." In Intelligent Visual Inspection, 156–79. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4613-1201-7_8.

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El Zant, Chawki, Quentin Charrier, Khaled Benfriha, and Patrick Le Men. "Enhanced Manufacturing Execution System “MES” Through a Smart Vision System." In Lecture Notes in Mechanical Engineering, 329–34. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70566-4_52.

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AbstractThe level of industrial performance is a vital issue for any company wishing to develop and acquire more market share. This article presents a novel approach to integrate intelligent visual inspection into “MES” control systems in order to gain performance. The idea is to adapt an intelligent image processing system via in-situ cameras to monitor the production system. The images are thus analyzed in real time via machine learning interpreting the visualized scene and interacting with some features of the MES system, such as maintenance, quality control, security, operations, etc. This novel technological brick, combined with the flexibility of production, contributes to optimizing the system in terms of autonomy and responsiveness to detect anomalies, already encountered, or even new ones. This smart visual inspection system is considered as a Cyber Physical System CPS brick integrated to the manufacturing system which will be considered an edge computing node in the final architecture of the platform. This smart CPS represents the 1st level of calculation and analysis in real time due to embedded intelligence. Cloud computing will be a perspective for us, which will represent the 2nd level of computation, in deferred time, in order to analyze the new anomalies encountered and identify potential solutions to integrate into MES. Ultimately, this approach strengthens the robustness of the control systems and increases the overall performance of industrial production.
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Avenhaus, Rudolf, and Morton J. Canty. "Inspection Games." In Computational Complexity, 1605–18. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-1800-9_103.

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Ashok, Pranav, Mathias Jackermeier, Jan Křetínský, Christoph Weinhuber, Maximilian Weininger, and Mayank Yadav. "dtControl 2.0: Explainable Strategy Representation via Decision Tree Learning Steered by Experts." In Tools and Algorithms for the Construction and Analysis of Systems, 326–45. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72013-1_17.

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AbstractRecent advances have shown how decision trees are apt data structures for concisely representing strategies (or controllers) satisfying various objectives. Moreover, they also make the strategy more explainable. The recent tool had provided pipelines with tools supporting strategy synthesis for hybrid systems, such as and . We present , a new version with several fundamentally novel features. Most importantly, the user can now provide domain knowledge to be exploited in the decision tree learning process and can also interactively steer the process based on the dynamically provided information. To this end, we also provide a graphical user interface. It allows for inspection and re-computation of parts of the result, suggesting as well as receiving advice on predicates, and visual simulation of the decision-making process. Besides, we interface model checkers of probabilistic systems, namely and and provide dedicated support for categorical enumeration-type state variables. Consequently, the controllers are more explainable and smaller.
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Conference papers on the topic "Inspection computation"

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Satpute, Manali R., and Sumati M. Jagdale. "Automatic fruit quality inspection system." In 2016 International Conference on Inventive Computation Technologies (ICICT). IEEE, 2016. http://dx.doi.org/10.1109/inventive.2016.7823207.

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Beyhaghi, Hedyeh, and Robert Kleinberg. "Pandora's Problem with Nonobligatory Inspection." In EC '19: ACM Conference on Economics and Computation. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3328526.3329626.

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Zhu, Jianxin. "New inverse computation for optical-absorption coefficient in semiconductor material." In Optics and Optoelectronic Inspection and Control: Techniques, Applications, and Instruments, edited by FeiJun Song, Frank Chen, Michael Y. Y. Hung, and H. M. Shang. SPIE, 2000. http://dx.doi.org/10.1117/12.402636.

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Ellefsen, Kai Olav, Herman A. Lepikson, and Jan C. Albiez. "Planning Inspection Paths through Evolutionary Multi-objective Optimization." In GECCO '16: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2908812.2908883.

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Biffl, Stefan, Marcos Kalinowski, and Dietmar Winkler. "Towards an experiment line on software inspection with human computation." In ICSE '18: 40th International Conference on Software Engineering. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3193965.3193971.

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Lee, Shih-Hsiung, and Chu-Sing Yang. "A Simple Remote Auxiliary Inspection System." In 2017 10th International Conference on Intelligent Computation Technology and Automation (ICICTA). IEEE, 2017. http://dx.doi.org/10.1109/icicta.2017.47.

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Liang, Ruiyu, Yanqiong Ding, Xuewu Zhang, and Jiasheng Chen. "Copper Strip Surface Defects Inspection Based on SVM-RBF." In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.271.

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Wang, Ping, Xuewu Zhang, Yan Mu, and Zhihui Wang. "The Copper Surface Defects Inspection System Based on Computer Vision." In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.273.

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Landa-Torres, Itziar, Jesus L. Lobo, Idoia Murua, Diana Manjarres, and Javier Del Ser. "Multi-objective heuristics applied to robot task planning for inspection plants." In 2017 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2017. http://dx.doi.org/10.1109/cec.2017.7969496.

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Harris, Nicholas, Siming Liu, Sushil J. Louis, and Jim Hung La. "A genetic algorithm for multi-robot routing in automated bridge inspection." In GECCO '19: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3319619.3321917.

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