Automated color correction for colorimetric applications using barcodes

[eng] Color-based sensor devices often offer qualitative solutions, where a material change its color from one color to another, and this is change is observed by a user who performs a manual reading. These materials change their color in response to changes in a certain physical or chemical magnitude. Nowadays, we can find colorimetric indicators with several sensing targets, such as: temperature, humidity, environmental gases, etc. The common approach to quantize these sensors is to place ad hoc electronic components, e.g., a reader device. With the rise of smartphone technology, the possibility to automatically acquire a digital image of those sensors and then compute a quantitative measure is near. By leveraging this measuring process to the smartphones, we avoid the use of ad hoc electronic components, thus reducing colorimetric application cost. However, there exists a challenge on how-to acquire the images of the colorimetric applications and how-to do it consistently, with the disparity of external factors affecting the measure, such as ambient light conditions or different camera modules. In this thesis, we tackle the challenges to digitize and quantize colorimetric applications, such as colorimetric indicators. We make a statement to use 2D barcodes, well-known computer vision patterns, as the base technology to overcome those challenges. We focus on four main challenges: (I) to capture barcodes on top of real-world challenging surfaces (bottles, food packages, etc.), which are the usual surface where colorimetric indicators are placed; (II) to define a new 2D barcode to embed colorimetric features in a back-compatible fashion; (III) to achieve image consistency when capturing images with smartphones by reviewing existent methods and proposing a new color correction method, based upon thin-plate splines mappings; and (IV) to demonstrate a specific application use case applied to a colorimetric indicator for sensing CO2 in the range of modified atmosphere packaging, MAP, one of the common food-packaging standards.[cat] Els dispositius de sensat basats en color, normalment ofereixen solucions qualitatives, en aquestes solucions un material canvia el seu color a un altre color, i aquest canvi de color és observat per un usuari que fa una mesura manual. Aquests materials canvien de color en resposta a un canvi en una magnitud física o química. Avui en dia, podem trobar indicadors colorimètrics que amb diferents objectius, per exemple: temperatura, humitat, gasos ambientals, etc. L'opció més comuna per quantitzar aquests sensors és l'ús d'electrònica addicional, és a dir, un lector. Amb l'augment de la tecnologia dels telèfons intel·ligents, la possibilitat d'automatitzar l'adquisició d'imatges digitals d'aquests sensors i després computar una mesura quantitativa és a prop. Desplaçant aquest procés de mesura als telèfons mòbils, evitem l'ús d'aquesta electrònica addicional, i així, es redueix el cost de l'aplicació colorimètrica. Tanmateix, existeixen reptes sobre com adquirir les imatges de les aplicacions colorimètriques i de com fer-ho de forma consistent, a causa de la disparitat de factors externs que afecten la mesura, com per exemple la llum ambient or les diferents càmeres utilitzades. En aquesta tesi, encarem els reptes de digitalitzar i quantitzar aplicacions colorimètriques, com els indicadors colorimètrics. Fem una proposició per utilitzar codis de barres en dues dimensions, que són coneguts patrons de visió per computador, com a base de la nostra tecnologia per superar aquests reptes. Ens focalitzem en quatre reptes principals: (I) capturar codis de barres sobre de superfícies del món real (ampolles, safates de menjar, etc.), que són les superfícies on usualment aquests indicadors colorimètrics estan situats; (II) definir un nou codi de barres en dues dimensions per encastar elements colorimètrics de forma retro-compatible; (III) aconseguir consistència en la captura d'imatges quan es capturen amb telèfons mòbils, revisant mètodes de correcció de color existents i proposant un nou mètode basat en transformacions geomètriques que utilitzen splines; i (IV) demostrar l'ús de la tecnologia en un cas específic aplicat a un indicador colorimètric per detectar CO2 en el rang per envasos amb atmosfera modificada, MAP, un dels estàndards en envasos de menjar.

G-ID: identifying 3D Prints using slicing parameters

We present G-ID, a method that utilizes the subtle patterns left by the 3D printing process to distinguish and identify objects that otherwise look similar to the human eye. The key idea is to mark different instances of a 3D model by varying slicing parameters that do not change the model geometry but can be detected as machine-readable differences in the print. As a result, G-ID does not add anything to the object but exploits the patterns appearing as a byproduct of slicing, an essential step of the 3D printing pipeline. We introduce the G-ID slicing & labeling interface that varies the settings for each instance, and the G-ID mobile app, which uses image processing techniques to retrieve the parameters and their associated labels from a photo of the 3D printed object. Finally, we evaluate our method’s accuracy under different lighting conditions, when objects were printed with different filaments and printers, and with pictures taken from various positions and angles

INVESTIGATING THE CONTRAST OF SURFACE MARKING ON DIFFERENT COLOR CONNECTORS FOR TELECOMMUNICATIONS NEEDS

The development of marking technologies for telecommunications connectors requires increasingly detailed information about their applications. One solution is to use QR codes that contain sufficient information about the connectors' applications. Accurate marking of connectors requires a precise marking system, such as a laser marking system. In this study, a Rofin PowerLine F20 Varia fiber laser was used to mark four different types of ABS plastic connectors in various colors. To achieve optimal marking for all four colors, three experiments were conducted to achieve contrasting marking and high roughness. Easy QR code reading was achieved with an average marking power of 3 W to 4.2 W, a laser marking speed of 300 mm/s to 500 mm/s, and a scanning frequency of 50 kHz to 70 kHz at a constant pulse duration of 8 ns and raster spacing of 50 µm. The microstructural changes and change in roughness were determined using a laser scanning microscope (Olympus OLS5000), which revealed structural changes on the surface and an increase in relative roughness from 39% to 76%. This experiment shows that different parameters of the laser marking mode are required for each color

Information embedding and retrieval in 3D printed objects

Deep learning and convolutional neural networks have become the main tools of computer vision. These techniques are good at using supervised learning to learn complex representations from data. In particular, under limited settings, the image recognition model now performs better than the human baseline. However, computer vision science aims to build machines that can see. It requires the model to be able to extract more valuable information from images and videos than recognition. Generally, it is much more challenging to apply these deep learning models from recognition to other problems in computer vision. This thesis presents end-to-end deep learning architectures for a new computer vision field: watermark retrieval from 3D printed objects. As it is a new area, there is no state-of-the-art on many challenging benchmarks. Hence, we first define the problems and introduce the traditional approach, Local Binary Pattern method, to set our baseline for further study. Our neural networks seem useful but straightfor- ward, which outperform traditional approaches. What is more, these networks have good generalization. However, because our research field is new, the problems we face are not only various unpredictable parameters but also limited and low-quality training data. To address this, we make two observations: (i) we do not need to learn everything from scratch, we know a lot about the image segmentation area, and (ii) we cannot know everything from data, our models should be aware what key features they should learn. This thesis explores these ideas and even explore more. We show how to use end-to-end deep learning models to learn to retrieve watermark bumps and tackle covariates from a few training images data. Secondly, we introduce ideas from synthetic image data and domain randomization to augment training data and understand various covariates that may affect retrieve real-world 3D watermark bumps. We also show how the illumination in synthetic images data to effect and even improve retrieval accuracy for real-world recognization applications

ИНТЕЛЛЕКТУАЛЬНЫЙ числовым программным ДЛЯ MIMD-компьютер

For most scientific and engineering problems simulated on computers the solving of problems of the computational mathematics with approximately given initial data constitutes an intermediate or a final stage. Basic problems of the computational mathematics include the investigating and solving of linear algebraic systems, evaluating of eigenvalues and eigenvectors of matrices, the solving of systems of non-linear equations, numerical integration of initial- value problems for systems of ordinary differential equations.Для більшості наукових та інженерних задач моделювання на ЕОМ рішення задач обчислювальної математики з наближено заданими вихідними даними складає проміжний або остаточний етап. Основні проблеми обчислювальної математики відносяться дослідження і рішення лінійних алгебраїчних систем оцінки власних значень і власних векторів матриць, рішення систем нелінійних рівнянь, чисельного інтегрування початково задач для систем звичайних диференціальних рівнянь.Для большинства научных и инженерных задач моделирования на ЭВМ решение задач вычислительной математики с приближенно заданным исходным данным составляет промежуточный или окончательный этап. Основные проблемы вычислительной математики относятся исследования и решения линейных алгебраических систем оценки собственных значений и собственных векторов матриц, решение систем нелинейных уравнений, численного интегрирования начально задач для систем обыкновенных дифференциальных уравнений

Inverse design of metamaterials via topology optimization

Metamaterials are artificial composites with micro-structures that are systematically designed such that the macroscopic behavior can accommodate particular functionalities or exhibit extraordinary properties, which are not commonly found in natural materials. Topology and geometry of micro-structures play an important role in characterizing the properties of the metamaterials. Inverse design of metamaterials via topology optimization methods offer new topological features and helps in achieving novel physical mechanism or high-performance functionalities. Inverse design is an iterative process, that involves numerical analysis and requires much computational resources. This dissertation proposes the methodology for designing metamaterials using topology optimization with level set functions and model order reduction methods. Level set method enables design with smooth boundaries, while the computational effort required in solving large linear system of equations is eliminated with reduced basis approximations. An example of the inverse design method from the dissertation is to find a unit cell structure that results in macroscopic properties with intended elastic modulus for instance, with negative Poisson's ratio. The other example is to enhance hydrophone performance in 1-3 piezoelectric composites. Numerical examples demonstrate that the methodology is computationally efficient and robust for designing metamaterials. Taking advantage of inverse design as a powerful tool in designing metamaterials, it is adopted in this dissertation for the waveguides design. The second part of this thesis aims to design phononic crystals that offer robust transport of mechanical waves on the interfaces. The propagating wave modes in plate-like structures are topologically protected edge states and are analogous to quantum valley hall effect and quantum spin hall effect in the electronic systems. The computational inverse design methodology adopted is through topology optimization using genetic algorithm to find optimized unit cell geometries resulting from objective functions based on band structures and wave modes. The optimized phononic crystals support wave propagation against backscattering inspite of the presence of defects.Metamaterialien sind künstliche Verbundwerkstoffe mit Mikrostrukturen, die systematisch so gestaltet sind, dass das makroskopische Verhalten besondere Funktionen oder außergewöhnliche Eigenschaften aufweist, die in natürlichen Materialien nicht üblich sind. Topologie und Geometrie der Mikrostrukturen spielen eine wichtige Rolle bei der Charakterisierung der Eigenschaften der Metamaterialien. Das inverse Design von Metamaterialien mittels Topologie-Optimierungsmethoden bietet neue topologische Eigenschaften und hilft bei der Erreichung neuartiger physikalischer Mechanismen oder Hochleistungsfunktionen. Inverses Design ist ein iterativer Prozess, der numerische Analysen beinhaltet und viel Rechenleistung erfordert. In dieser Dissertation wird eine Methodik für den Entwurf von Metamaterialien unter Verwendung von Topologieoptimierung mit Level-Set-Funktionen und Methoden zur Reduzierung der Modellordnung vorgeschlagen. Die Level-Set-Methode ermöglicht ein Design mit glatten Grenzen, während der Rechenaufwand, der für die Lösung großer linearer Gleichungssysteme erforderlich ist, durch reduzierte Basisapproximationen entfällt. Ein Beispiel für die inverse Entwurfsmethode aus der Dissertation ist die Suche nach einer Einheitszellenstruktur, die zu makroskopischen Eigenschaften mit beabsichtigtem Elastizitätsmodul führt, beispielsweise mit negativer Poissonzahl. Ein anderes Beispiel ist die Verbesserung der Leistung von Hydrophonen in 1-3 piezoelektrischen Verbundwerkstoffen. Numerische Beispiele zeigen, dass die Methodik für die Entwicklung von Metamaterialien rechnerisch effizient und robust ist. Die Vorteile des inversen Designs als leistungsfähiges Werkzeug bei der Entwicklung von Metamaterialien werden in dieser Dissertation für die Entwicklung von Wellenleitern genutzt. Der zweite Teil dieser Arbeit zielt darauf ab, phononische Kristalle zu entwerfen, die einen robusten Transport von mechanischen Wellen an den Grenzflächen ermöglichen. Die sich ausbreitenden Wellenmoden in plattenförmigen Strukturen sind topologisch geschützte Randzustände und entsprechen dem Quanten-Tal-Hall-Effekt und dem Quanten-Spin-Hall-Effekt in elektronischen Systemen. Die angewandte rechnerische inverse Entwurfsmethodik besteht in der Topologieoptimierung mit Hilfe eines genetischen Algorithmus, um optimierte Einheitszellengeometrien zu finden, die sich aus Zielfunktionen auf der Grundlage von Bandstrukturen und Wellenmoden ergeben. Die optimierten phononischen Kristalle unterstützen die Wellenausbreitung trotz des Vorhandenseins von Defekten gegen Rückstreuung

Automation and Robotics: Latest Achievements, Challenges and Prospects

This SI presents the latest achievements, challenges and prospects for drives, actuators, sensors, controls and robot navigation with reverse validation and applications in the field of industrial automation and robotics. Automation, supported by robotics, can effectively speed up and improve production. The industrialization of complex mechatronic components, especially robots, requires a large number of special processes already in the pre-production stage provided by modelling and simulation. This area of research from the very beginning includes drives, process technology, actuators, sensors, control systems and all connections in mechatronic systems. Automation and robotics form broad-spectrum areas of research, which are tightly interconnected. To reduce costs in the pre-production stage and to reduce production preparation time, it is necessary to solve complex tasks in the form of simulation with the use of standard software products and new technologies that allow, for example, machine vision and other imaging tools to examine new physical contexts, dependencies and connections

Advanced Applications of Rapid Prototyping Technology in Modern Engineering

Rapid prototyping (RP) technology has been widely known and appreciated due to its flexible and customized manufacturing capabilities. The widely studied RP techniques include stereolithography apparatus (SLA), selective laser sintering (SLS), three-dimensional printing (3DP), fused deposition modeling (FDM), 3D plotting, solid ground curing (SGC), multiphase jet solidification (MJS), laminated object manufacturing (LOM). Different techniques are associated with different materials and/or processing principles and thus are devoted to specific applications. RP technology has no longer been only for prototype building rather has been extended for real industrial manufacturing solutions. Today, the RP technology has contributed to almost all engineering areas that include mechanical, materials, industrial, aerospace, electrical and most recently biomedical engineering. This book aims to present the advanced development of RP technologies in various engineering areas as the solutions to the real world engineering problems

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Harnessing Simulated Data with Graphs

Physically accurate simulations allow for unlimited exploration of arbitrarily crafted environments. From a scientific perspective, digital representations of the real world are useful because they make it easy validate ideas. Virtual sandboxes allow observations to be collected at-will, without intricate setting up for measurements or needing to wait on the manufacturing, shipping, and assembly of physical resources. Simulation techniques can also be utilized over and over again to test the problem without expending costly materials or producing any waste. Remarkably, this freedom to both experiment and generate data becomes even more powerful when considering the rising adoption of data-driven techniques across engineering disciplines. These are systems that aggregate over available samples to model behavior, and thus are better informed when exposed to more data. Naturally, the ability to synthesize limitless data promises to make approaches that benefit from datasets all the more robust and desirable. However, the ability to readily and endlessly produce synthetic examples also introduces several new challenges. Data must be collected in an adaptive format that can capture the complete diversity of states achievable in arbitrary simulated configurations while too remaining amenable to downstream applications. The quantity and zoology of observations must also straddle a range which prevents overfitting but is descriptive enough to produce a robust approach. Pipelines that naively measure virtual scenarios can easily be overwhelmed by trying to sample an infinite set of available configurations. Variations observed across multiple dimensions can quickly lead to a daunting expansion of states, all of which must be processed and solved. These and several other concerns must first be addressed in order to safely leverage the potential of boundless simulated data. In response to these challenges, this thesis proposes to wield graphs in order to instill structure over digitally captured data, and curb the growth of variables. The paradigm of pairing data with graphs introduced in this dissertation serves to enforce consistency, localize operators, and crucially factor out any combinatorial explosion of states. Results demonstrate the effectiveness of this methodology in three distinct areas, each individually offering unique challenges and practical constraints, and together showcasing the generality of the approach. Namely, studies observing state-of-the-art contributions in design for additive manufacturing, side-channel security threats, and large-scale physics based contact simulations are collectively achieved by harnessing simulated datasets with graph algorithms