271 research outputs found

    Multiscale Edge Detection using a Finite Element Framework for Hexagonal Pixel-based Images

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    Local Binary Patterns on Hexagonal Image Structure

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    Local binary pattern (LBP) was designed and widely used for efficient texture classification. It has been used for face recognition and has potential applications in many other research areas such as human detection. LBP provides a simple and effective way to represent patterns. Uniform LBPs play an important role for LBP-based pattern /object recognition as they include majority of LBPs. In this paper, we present LBP codes on hexagonal image structure. We show that LBPs defined on hexagonal structure have higher percentages of uniform LBPs that will lead to a more efficient and accurate recognition scheme for image classification

    Hexagonal structure for intelligent vision

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    Using hexagonal grids to represent digital images have been studied for more than 40 years. Increased processing capabilities of graphic devices and recent improvements in CCD technology have made hexagonal sampling attractive for practical applications and brought new interests on this topic. The hexagonal structure is considered to be preferable to the rectangular structure due to its higher sampling efficiency, consistent connectivity and higher angular resolution and is even proved to be superior to square structure in many applications. Since there is no mature hardware for hexagonal-based image capture and display, square to hexagonal image conversion has to be done before hexagonal-based image processing. Although hexagonal image representation and storage has not yet come to a standard, experiments based on existing hexagonal coordinate systems have never ceased. In this paper, we firstly introduced general reasons that hexagonally sampled images are chosen for research. Then, typical hexagonal coordinates and addressing schemes, as well as hexagonal based image processing and applications, are fully reviewed. © 2005 IEEE

    Object information based on marker recognition

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    Vision Science and Technology at NASA: Results of a Workshop

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    A broad review is given of vision science and technology within NASA. The subject is defined and its applications in both NASA and the nation at large are noted. A survey of current NASA efforts is given, noting strengths and weaknesses of the NASA program

    Automated freeform assembly of threaded fasteners

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    Over the past two decades, a major part of the manufacturing and assembly market has been driven by its customer requirements. Increasing customer demand for personalised products create the demand for smaller batch sizes, shorter production times, lower costs, and the flexibility to produce families of products - or different parts - with the same sets of equipment. Consequently, manufacturing companies have deployed various automation systems and production strategies to improve their resource efficiency and move towards right-first-time production. However, many of these automated systems, which are involved with robot-based, repeatable assembly automation, require component- specific fixtures for accurate positioning and extensive robot programming, to achieve flexibility in their production. Threaded fastening operations are widely used in assembly. In high-volume production, the fastening processes are commonly automated using jigs, fixtures, and semi-automated tools. This form of automation delivers reliable assembly results at the expense of flexibility and requires component variability to be adequately controlled. On the other hand, in low- volume, high- value manufacturing, fastening processes are typically carried out manually by skilled workers. This research is aimed at addressing the aforementioned issues by developing a freeform automated threaded fastener assembly system that uses 3D visual guidance. The proof-of-concept system developed focuses on picking up fasteners from clutter, identifying a hole feature in an imprecisely positioned target component and carry out torque-controlled fastening. This approach has achieved flexibility and adaptability without the use of dedicated fixtures and robot programming. This research also investigates and evaluates different 3D imaging technology to identify the suitable technology required for fastener assembly in a non-structured industrial environment. The proposed solution utilises the commercially available technologies to enhance the precision and speed of identification of components for assembly processes, thereby improving and validating the possibility of reliably implementing this solution for industrial applications. As a part of this research, a number of novel algorithms are developed to robustly identify assembly components located in a random environment by enhancing the existing methods and technologies within the domain of the fastening processes. A bolt identification algorithm was developed to identify bolts located in a random clutter by enhancing the existing surface-based matching algorithm. A novel hole feature identification algorithm was developed to detect threaded holes and identify its size and location in 3D. The developed bolt and feature identification algorithms are robust and has sub-millimetre accuracy required to perform successful fastener assembly in industrial conditions. In addition, the processing time required for these identification algorithms - to identify and localise bolts and hole features - is less than a second, thereby increasing the speed of fastener assembly

    Noisy images edge detection: Ant colony optimization algorithm

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    The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy images with Gaussian noise and salt and pepper noise. As the image edge frequencies are close to the noise frequency band, the edge detection using the conventional edge detection methods is challenging. The movement of ants depends on local discrepancy of image’s intensity value. The simulation results compared with existing conventional methods and are provided to support the superior performance of ACO algorithm in noisy images edge detection. Canny, Sobel and Prewitt operator have thick, non continuous edges and with less clear image content. But the applied method gives thin and clear edges

    Influence of transcrystalline layer on finite element mesoscale modeling of polyamide 6 based single polymer laminate composites

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    This study presents a novel approach for finite element modeling of the elastic behavior of a plain-woven reinforced single polymer laminate composites (WSPC) based on polyamide 6 (PA6). These composites are produced via compression molding of PA6 woven textile structures that are powder-coated by anionic PA6 microparticles. Morphological and structural analysis complemented by electron microscopy, image processing and X-ray diffraction suggest the presence of transcrystalline layer (TCL) at the matrix-reinforcement interface. Having in mid this experimental fact, a novel procedure is developed for finite level discretization of TCL in the representative volume element (RVE) during tensile straining. The procedure correlates the material properties with the overall load applied, thus adequately modelling the tensile behavior of the WSPC based on the constituent materials. The stress field along the elements of the RVE model is studied while the tensile loads were applied in two principal directions. A good agreement between the real mechanical behavior and that calculated based on the model was demonstrated.IPC and 2C2T gratefully acknowledge the support of the project TSSiPRO-NORTE-01-0145-FEDER-000015 funded by the regional operational program NORTE 2020, under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund. The authors affiliated to 2C2T acknowledge also partial funding from FCT - Fundação para a Ciência e a Tecnologia within the projects POCI- 01-0145-FEDER-007136 and UID/CTM/00264. S.D. Tohidi thanks to FCT for the PhD Grant SFRH/BD/94759/2013. N. Dourado acknowledges FCT for the financial support through the projects UID/EEA/04436/2013 and POCI-01-0145-FEDER-006941. M. Rezazadeh acknowledges the support provided by FEDER and FCT funds through project POCI-01-0145-FEDER-029485. N.Q. Quyền thanks for the financial support of FCT through the project PESTUID/CTM/00264. A. Zille also acknowledges the FCT Investigator Research contract IF/00071/2015. S. Hesseler and T. Gries gratefully acknowledge the financial support of German Science Foundation (DFG) through the project RE1057/41. Z. Z. Denchev and N. V. Dencheva acknowledge the support by National Funds through FCT, project UID/CTM/50025/2019. N. Dencheva is also grateful for the financial support of FCT in the frames of the strategic project UID/CTM/50025/2013 and the personal program-contract CTTI-51/18-IP

    Design and Development of Sensor Integrated Robotic Hand

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    Most of the automated systems using robots as agents do use few sensors according to the need. However, there are situations where the tasks carried out by the end-effector, or for that matter by the robot hand needs multiple sensors. The hand, to make the best use of these sensors, and behave autonomously, requires a set of appropriate types of sensors which could be integrated in proper manners. The present research work aims at developing a sensor integrated robot hand that can collect information related to the assigned tasks, assimilate there correctly and then do task action as appropriate. The process of development involves selection of sensors of right types and of right specification, locating then at proper places in the hand, checking their functionality individually and calibrating them for the envisaged process. Since the sensors need to be integrated so that they perform in the desired manner collectively, an integration platform is created using NI PXIe-1082. A set of algorithm is developed for achieving the integrated model. The entire process is first modelled and simulated off line for possible modification in order to ensure that all the sensors do contribute towards the autonomy of the hand for desired activity. This work also involves design of a two-fingered gripper. The design is made in such a way that it is capable of carrying out the desired tasks and can accommodate all the sensors within its fold. The developed sensor integrated hand has been put to work and its performance test has been carried out. This hand can be very useful for part assembly work in industries for any shape of part with a limit on the size of the part in mind. The broad aim is to design, model simulate and develop an advanced robotic hand. Sensors for pick up contacts pressure, force, torque, position, surface profile shape using suitable sensing elements in a robot hand are to be introduced. The hand is a complex structure with large number of degrees of freedom and has multiple sensing capabilities apart from the associated sensing assistance from other organs. The present work is envisaged to add multiple sensors to a two-fingered robotic hand having motion capabilities and constraints similar to the human hand. There has been a good amount of research and development in this field during the last two decades a lot remains to be explored and achieved. The objective of the proposed work is to design, simulate and develop a sensor integrated robotic hand. Its potential applications can be proposed for industrial environments and in healthcare field. The industrial applications include electronic assembly tasks, lighter inspection tasks, etc. Application in healthcare could be in the areas of rehabilitation and assistive techniques. The work also aims to establish the requirement of the robotic hand for the target application areas, to identify the suitable kinds and model of sensors that can be integrated on hand control system. Functioning of motors in the robotic hand and integration of appropriate sensors for the desired motion is explained for the control of the various elements of the hand. Additional sensors, capable of collecting external information and information about the object for manipulation is explored. Processes are designed using various software and hardware tools such as mathematical computation MATLAB, OpenCV library and LabVIEW 2013 DAQ system as applicable, validated theoretically and finally implemented to develop an intelligent robotic hand. The multiple smart sensors are installed on a standard six degree-of-freedom industrial robot KAWASAKI RS06L articulated manipulator, with the two-finger pneumatic SHUNK robotic hand or designed prototype and robot control programs are integrated in such a manner that allows easy application of grasping in an industrial pick-and-place operation where the characteristics of the object can vary or are unknown. The effectiveness of the actual recommended structure is usually proven simply by experiments using calibration involving sensors and manipulator. The dissertation concludes with a summary of the contribution and the scope of further work
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