{"product_id":"image-segmentation-isbn-9781119859000","title":"Image Segmentation","description":"\u003cb\u003eImage Segmentation\u003c\/b\u003e \u003cp\u003e\u003cb\u003eSummarizes and improves new theory, methods, and applications of current image segmentation approaches, written by leaders in the field \u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eThe process of image segmentation divides an image into different regions based on the characteristics of pixels, resulting in a simplified image that can be more efficiently analyzed. Image segmentation has wide applications in numerous fields ranging from industry detection and bio-medicine to intelligent transportation and architecture.  \u003c\/p\u003e\u003cp\u003e\u003ci\u003eImage Segmentation: Principles, Techniques, and Applications\u003c\/i\u003e is an up-to-date collection of recent techniques and methods devoted to the field of computer vision. Covering fundamental concepts, new theories and approaches, and a variety of practical applications including medical imaging, remote sensing, fuzzy clustering, and watershed transform. In-depth chapters present innovative methods developed by the authors—such as convolutional neural networks, graph convolutional networks, deformable convolution, and model compression—to assist graduate students and researchers apply and improve image segmentation in their work.  \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDescribes basic principles of image segmentation and related mathematical methods such as clustering, neural networks, and mathematical morphology.\u003c\/li\u003e \u003cli\u003eIntroduces new methods for achieving rapid and accurate image segmentation based on classic image processing and machine learning theory.\u003c\/li\u003e \u003cli\u003ePresents techniques for improved convolutional neural networks for scene segmentation, object recognition, and change detection, etc.\u003c\/li\u003e \u003cli\u003eHighlights the effect of image segmentation in various application scenarios such as traffic image analysis, medical image analysis, remote sensing applications, and material analysis, etc.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003ci\u003eImage Segmentation: Principles, Techniques, and Applications\u003c\/i\u003e is an essential resource for undergraduate and graduate courses such as image and video processing, computer vision, and digital signal processing, as well as researchers working in computer vision and image analysis looking to improve their techniques and methods. \u003c\/p\u003e\u003cp\u003ePreface\u003c\/p\u003e \u003cp\u003eAbout the Authors\u003c\/p\u003e \u003cp\u003eList of Abbreviations\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart One: Principle \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1   Introduction to Image Segmentation\u003c\/p\u003e \u003cp\u003e2   Principles of Clustering\u003c\/p\u003e \u003cp\u003e3   Principles of Mathematical Morphology\u003c\/p\u003e \u003cp\u003e4   Principles of Neural Network\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart Two: Methods\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5   Fast and Robust Image Segmentation Using Clustering\u003c\/p\u003e \u003cp\u003e6   Fast Image Segmentation Using Watershed Transform\u003c\/p\u003e \u003cp\u003e7   Superpixel-based Fast Image Segmentation\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart Three:  Application\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8   Image Segmentation for Traffic Scene Analysis\u003c\/p\u003e \u003cp\u003e9   Image Segmentation for Medical Analysis\u003c\/p\u003e \u003cp\u003e10 Image Segmentation for Remote Sensing Analysis\u003c\/p\u003e \u003cp\u003e11 Image Segmentation for Material Analysis\u003c\/p\u003e \u003cp\u003e\u003cb\u003eTao Lei,\u003c\/b\u003e Professor, School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, China. His research interests include image processing, pattern recognition, and machine learning and he has authored and co-authored more than 100 research papers. \u003c\/p\u003e \u003cp\u003e\u003cb\u003eAsoke K. Nandi,\u003c\/b\u003e Professor, Department of Electronic and Electrical Engineering, Brunel University London, UK. He is also Distinguished Visiting Professor, Xi’an Jiaotong University, China. Professor Nandi has authored over 600 technical publications, including 280 journal papers as well as five books.  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eSummarizes and improves new theory, methods, and applications of current image segmentation approaches, written by leaders in the field \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe process of image segmentation divides an image into different regions based on the characteristics of pixels, resulting in a simplified image that can be more efficiently analyzed. Image segmentation has wide applications in numerous fields ranging from industry detection and bio-medicine to intelligent transportation and architecture.  \u003c\/p\u003e\u003cp\u003e\u003ci\u003eImage Segmentation: Principles, Techniques, and Applications\u003c\/i\u003e is an up-to-date collection of recent techniques and methods devoted to the field of computer vision. Covering fundamental concepts, new theories and approaches, and a variety of practical applications including medical imaging, remote sensing, fuzzy clustering, and watershed transform. In-depth chapters present innovative methods developed by the authors—such as convolutional neural networks, graph convolutional networks, deformable convolution, and model compression—to assist graduate students and researchers apply and improve image segmentation in their work.  \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDescribes basic principles of image segmentation and related mathematical methods such as clustering, neural networks, and mathematical morphology.\u003c\/li\u003e \u003cli\u003eIntroduces new methods for achieving rapid and accurate image segmentation based on classic image processing and machine learning theory.\u003c\/li\u003e \u003cli\u003ePresents techniques for improved convolutional neural networks for scene segmentation, object recognition, and change detection, etc.\u003c\/li\u003e \u003cli\u003eHighlights the effect of image segmentation in various application scenarios such as traffic image analysis, medical image analysis, remote sensing applications, and material analysis, etc.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003ci\u003eImage Segmentation: Principles, Techniques, and Applications\u003c\/i\u003e is an essential resource for undergraduate and graduate courses such as image and video processing, computer vision, and digital signal processing, as well as researchers working in computer vision and image analysis looking to improve their techniques and methods.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989401452773,"sku":"NP9781119859000","price":145.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119859000.jpg?v=1761783968","url":"https:\/\/k12savings.com\/products\/image-segmentation-isbn-9781119859000","provider":"K12savings","version":"1.0","type":"link"}