Object Recognition In Noisy Natural Images
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Object Recognition In Noisy Natural Images
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Author : Prasanna Kannappan
language : en
Publisher:
Release Date : 2017
Object Recognition In Noisy Natural Images written by Prasanna Kannappan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Autonomous robotic systems can operate in an unsupervised manner over remote or potentially dangerous domains. Object recognition is an important trait required for a robotic system to achieve autonomy. The task of object recognition involves understanding and labeling the different components in a robot's environment. This task becomes complicated for robots that operate in unstructured natural environments, like forests or deep sea, due to noise in sensor measurements. Noisy sensor measurements can potentially affect a robot's perception of the world. To avoid being misled by corrupted measurements, robots need to possess robust object recognition capabilities that can handle noise in sensor measurements. Such robust object recognition capabilities are valuable for processing large natural image datasets. One such case of image datasets are the underwater imagery data gathered by marine scientists and oceanographers; there, automatic object recognition capabilities could be invaluable. Such a capability would enable the automatic analysis of these datasets to understand natural phenomena, for instance to recognize different organisms of interest. Sifting through such big datasets, which can range into millions of images, and making inferences based on this data, is evolving into one of the biggest challenges in the field research community. This motivates the need for automated object recognition and image analysis tools. ☐ This dissertation focusses on object recognition techniques capable of operating in noisy natural environments. A series underwater object recognition problems have been solved as means to validate the developed object recognition algorithms. Each technique was developed to complement the shortcomings of the existing tools available to the research community. At first, eigen-value based shape descriptors were tasked to solve a submerged subway car recognition problem. Despite being successful in solving this problem, the eigen-value shape descriptor method cannot leverage textural cues for object identification. This primary drawback, among other shortcomings, lead to the development of a multi-layered object recognition architecture. This multilayered architecture was tested on an scallop enumeration problem. 60-70% of scallop instances were successfully identified. To improve the machine learning classifier of this multi-layered framework, and also to minimize false positives, a multi-view object classification approach is proposed. This multi-view approach combines histogram-based global cues from a series of images of a target, captured from different heights, to construct a machine learning classifier. This multi-view method was successful in classifying all specimens in the available dataset. In addition to the developed object recognition methods, a low cost ROV, named CoopROV, was designed for underwater data collection to support research experiments.
Natural Object Recognition
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Author : Thomas M. Strat
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Natural Object Recognition written by Thomas M. Strat and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Natural Object Recognition presents a totally new approach to the automation of scene understanding. Rather than attempting to construct highly specialized algorithms for recognizing physical objects, as is customary in modern computer vision research, the application and subsequent evaluation of large numbers of relatively straightforward image processing routines is used to recognize natural features such as trees, bushes, and rocks. The use of contextual information is the key to simplifying the problem to the extent that well understood algorithms give reliable results in ground-level, outdoor scenes.
Denoising Of Photographic Images And Video
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Author : Marcelo Bertalmío
language : en
Publisher: Springer
Release Date : 2018-09-10
Denoising Of Photographic Images And Video written by Marcelo Bertalmío and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-10 with Computers categories.
This unique text/reference presents a detailed review of noise removal for photographs and video. An international selection of expert contributors provide their insights into the fundamental challenges that remain in the field of denoising, examining how to properly model noise in real scenarios, how to tailor denoising algorithms to these models, and how to evaluate the results in a way that is consistent with perceived image quality. The book offers comprehensive coverage from problem formulation to the evaluation of denoising methods, from historical perspectives to state-of-the-art algorithms, and from fast real-time techniques that can be implemented in-camera to powerful and computationally intensive methods for off-line processing. Topics and features: describes the basic methods for the analysis of signal-dependent and correlated noise, and the key concepts underlying sparsity-based image denoising algorithms; reviews the most successful variational approaches for image reconstruction, and introduces convolutional neural network-based denoising methods; provides an overview of the use of Gaussian priors for patch-based image denoising, and examines the potential of internal denoising; discusses selection and estimation strategies for patch-based video denoising, and explores how noise enters the imaging pipeline; surveys the properties of real camera noise, and outlines a fast approximation of nonlocal means filtering; proposes routes to improving denoising results via indirectly denoising a transform of the image, considering the right noise model and taking into account the perceived quality of the outputs. This concise and clearly written volume will be of great value to researchers and professionals working in image processing and computer vision. The book will also serve as an accessible reference for advanced undergraduate and graduate students in computer science, applied mathematics, and related fields. "The relentless quest for higher image resolution, greater ISO sensitivity, faster frame rates and smaller imaging sensors in digital imaging and videography has demanded unprecedented innovation and improvement in noise reduction technologies. This book provides a comprehensive treatment of all aspects of image noise including noise modelling, state of the art noise reduction technologies and visual perception and quantitative evaluation of noise.” Geoff Woolfe, Former President of The Society for Imaging Science and Technology. "This book on denoising of photographic images and video is the most comprehensive and up-to-date account of this deep and classic problem of image processing. The progress on its solution is being spectacular. This volume therefore is a must read for all engineers and researchers concerned with image and video quality." Jean-Michel Morel, Professor at Ecole Normale Supérieure de Cachan, France.
Object Recognition In Images Degraded By Gaussian And Photon Limited Noise
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Author : Ahmad Abu-Naser
language : en
Publisher:
Release Date : 2001
Object Recognition In Images Degraded By Gaussian And Photon Limited Noise written by Ahmad Abu-Naser and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.
Fast Object Recognition In Noisy Images Using Simulated Annealing
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Author : M. Betke
language : en
Publisher:
Release Date : 1994
Fast Object Recognition In Noisy Images Using Simulated Annealing written by M. Betke and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.
Fast Object Recognition In Noisy Images Using Simulated Annealing
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Author : M. Betke
language : en
Publisher:
Release Date : 1994
Fast Object Recognition In Noisy Images Using Simulated Annealing written by M. Betke and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.
Object Recognition Based On Impulse Restoration For Images In Gaussian Noise
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Author : Ahmed Abu-Naser
language : en
Publisher:
Release Date : 1996
Object Recognition Based On Impulse Restoration For Images In Gaussian Noise written by Ahmed Abu-Naser and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with categories.
Object Recognition Of Digital Images In Wavelet Neural Network
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Author : Arul Murugan R
language : en
Publisher: Archers & Elevators Publishing House
Release Date :
Object Recognition Of Digital Images In Wavelet Neural Network written by Arul Murugan R and has been published by Archers & Elevators Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on with Antiques & Collectibles categories.
Small Object Detection In Noisy And Cluttered Images
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Author : Xin Sheng
language : en
Publisher:
Release Date : 1999
Small Object Detection In Noisy And Cluttered Images written by Xin Sheng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Image processing categories.
Object Recognition From Range Images
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Author : Richard Lee Hoffman
language : en
Publisher:
Release Date : 1986
Object Recognition From Range Images written by Richard Lee Hoffman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Computer vision categories.