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Report On 2D Dimensional Nature Of Image

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Added on  2021-04-16

Report On 2D Dimensional Nature Of Image

   Added on 2021-04-16

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A report on 2D dimensional nature of image and rate of capturing image data with the NaoNameInstitutionProfessorCourseDate
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Problem statementThere has been controversy over the planning and navigation of Robots through itsspecific environment. In order to create an autonomous planning, clear understanding of theenvironment is required. A computer vision system can be used to provide any pertinentinformation about required robot environment (Zhang et al, 2013). Captured data would helprobots to interact with its agents while navigating through the environment in order to trackthem. In this regard, the concept of computer vision systems and robotic visual tracking is ofgreat importance (Moreno et al, 2012). To interact with the environment, a robot makes use ofimages that contain useful data about objects properties such as its positions, sizes, distance, andvolatility. When capturing required data, the 2-D nature of capturing images and the rate used tocapture these images have been of great challenge (Maini & Aggarwal, 2009). The problem ofcapturing images is complicated by the lack of computer vision signals that can process andtransmit image data at the optimal rate. Therefore, this paper tries to investigate the nature ofimages and the rate at which required robotic image data is captured through the use of computervision. Background informationComputer vision relies mainly on image processing and analysis that tends to emphasison 2 D images to capture and process robotic required data (Barakova & Lourens, 2010). Theprocess tries to visualize on how to transform images through the use of pixel, edge removal, andapplication of 2D images. The important aspect to note in this case is that, computer vision doesnot require any pre-determined complex assumptions to capture quality image data (Obwald,Hornung & Bennewitz, 2010). Mainly, a robot should be able to determine the nature of the
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image as depicted in its operational environment in order to process image characteristics. Tomake robot have the capability to process and capture pertinent image information, both controltheory and sensor technology should be incorporated. To make the real-time process of theimage data efficient, the 2D image processing should focus on software and hardwareimplementation (Faragasso et al, 2013). Efficient processing of image signals makes it possiblefor the robot to navigate through environment swiftly. As system implementation part focuses onimage processing, the concept of pattern recognition is very important. It helps robots todetermine the nature and shape of an image by using various dynamic methods to extract imagedata. InvestigationsTo better the understanding of image processing and image data collection, the followingresearch was done. In this case, only one experiment would be used. ObjectiveThe main goal of the study was to determine how computer vision is used to detect andprocess image data in robots. In this study, the effector was the head and the whole body. Solution design
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