Study Of Object Recognition And Identification Based On Shape And Texture Analysis
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Study Of Object Recognition And Identification Based On Shape And Texture Analysis
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Author : Guanqi Wang
language : en
Publisher:
Release Date : 2012
Study Of Object Recognition And Identification Based On Shape And Texture Analysis written by Guanqi Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Handbook Of Pattern Recognition And Computer Vision
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Author : C. H. Chen
language : en
Publisher: World Scientific
Release Date : 1999
Handbook Of Pattern Recognition And Computer Vision written by C. H. Chen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.
The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
Feature Dimension Reduction For Content Based Image Identification
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Author : Das, Rik
language : en
Publisher: IGI Global
Release Date : 2018-06-29
Feature Dimension Reduction For Content Based Image Identification written by Das, Rik and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-29 with Computers categories.
Image data has portrayed immense potential as a foundation of information for numerous applications. Recent trends in multimedia computing have witnessed a rapid growth in digital image collections, resulting in a need for increased image data management. Feature Dimension Reduction for Content-Based Image Identification is a pivotal reference source that explores the contemporary trends and techniques of content-based image recognition. Including research covering topics such as feature extraction, fusion techniques, and image segmentation, this book explores different theories to facilitate timely identification of image data and managing, archiving, maintaining, and extracting information. This book is ideally designed for engineers, IT specialists, researchers, academicians, and graduate-level students seeking interdisciplinary research on image processing and analysis.
Object Recognition
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Author : M. Bennamoun
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-12-12
Object Recognition written by M. Bennamoun 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 2001-12-12 with Computers categories.
Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.
Research In Shape Analysis
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Author : Asli Genctav
language : en
Publisher: Springer
Release Date : 2018-05-17
Research In Shape Analysis written by Asli Genctav and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-17 with Mathematics categories.
Based on the second Women in Shape (WiSH) workshop held in Sirince, Turkey in June 2016, these proceedings offer the latest research on shape modeling and analysis and their applications. The 10 peer-reviewed articles in this volume cover a broad range of topics, including shape representation, shape complexity, and characterization in solving image-processing problems. While the first six chapters establish understanding in the theoretical topics, the remaining chapters discuss important applications such as image segmentation, registration, image deblurring, and shape patterns in digital fabrication. The authors in this volume are members of the WiSH network and their colleagues, and most were involved in the research groups formed at the workshop. This volume sheds light on a variety of shape analysis methods and their applications, and researchers and graduate students will find it to be an invaluable resource for further research in the area.
Advancement Of Deep Learning And Its Applications In Object Detection And Recognition
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Author : Roohie Naaz Mir
language : en
Publisher: CRC Press
Release Date : 2023-05-10
Advancement Of Deep Learning And Its Applications In Object Detection And Recognition written by Roohie Naaz Mir and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-10 with Computers categories.
Object detection is a basic visual identification problem in computer vision that has been explored extensively over the years. Visual object detection seeks to discover objects of specific target classes in a given image with pinpoint accuracy and apply a class label to each object instance. Object recognition strategies based on deep learning have been intensively investigated in recent years as a result of the remarkable success of deep learning-based image categorization. In this book, we go through in detail detector architectures, feature learning, proposal generation, sampling strategies, and other issues that affect detection performance. The book describes every newly proposed novel solution but skips through the fundamentals so that readers can see the field's cutting edge more rapidly. Moreover, unlike prior object detection publications, this project analyses deep learning-based object identification methods systematically and exhaustively, and also gives the most recent detection solutions and a collection of noteworthy research trends. The book focuses primarily on step-by-step discussion, an extensive literature review, detailed analysis and discussion, and rigorous experimentation results. Furthermore, a practical approach is displayed and encouraged.
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.
Modern Trends In Diatom Identification
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Author : Gabriel Cristóbal
language : en
Publisher: Springer Nature
Release Date : 2020-05-28
Modern Trends In Diatom Identification written by Gabriel Cristóbal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-28 with Science categories.
High-resolution images of phytoplankton cells such as diatoms or desmids, which are useful for monitoring water quality, can now be provided by digital microscopes, facilitating the automated analysis and identification of specimens. Conventional approaches are based on optical microscopy; however, manual image analysis is impractical due to the huge diversity of this group of microalgae and its great morphological plasticity. As such, there is a need for automated recognition techniques for diagnostic tools (e.g. environmental monitoring networks, early warning systems) to improve the management of water resources and decision-making processes. Describing the entire workflow of a bioindicator system, from capture, analysis and identification to the determination of quality indices, this book provides insights into the current state-of-the-art in automatic identification systems in microscopy.
Encyclopedia Of Biometrics
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Author : Stan Z. Li
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-08-27
Encyclopedia Of Biometrics written by Stan Z. Li 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 2009-08-27 with Computers categories.
With an A–Z format, this encyclopedia provides easy access to relevant information on all aspects of biometrics. It features approximately 250 overview entries and 800 definitional entries. Each entry includes a definition, key words, list of synonyms, list of related entries, illustration(s), applications, and a bibliography. Most entries include useful literature references providing the reader with a portal to more detailed information.
Representations Of Shape In Object Recognition And Long Term Visual Memory
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Author :
language : en
Publisher:
Release Date : 1996
Representations Of Shape In Object Recognition And Long Term Visual Memory written by 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.
Our research has focused on the mechanisms used in visual object recognition. Recent psychophysical results suggest that human perceivers often rely on viewpoint-specific (view-based) representations in conjunction with normalization procedures. Over the past year we have explored the degree to which view-based representations are also appearance based. Specifically we have found that visual recognition across many tasks is sensitive to changes in image properties such as illumination, color, and material (texture). These results indicate that object representations are information rich and that abstract part-based structural-descriptions will not account for much of human recognition performance. Other work has focused on how view-based representations are organized and function across changes in viewpoint. Using 3D stimuli rotated in depth we have investigated the role of task, ranging from basic-level to subordinate-level discriminations, how view-based representations generalize from known members of a class to unfamiliar members of that class, and how perceptual expertise is acquired and influences recognition strategies. We have also been in vestigating the mechanisms used for discriminating between highly similar objects, : e.g., faces.