Jayanta Mukhopadhyay – författare

Exploring theories and applications developed during the last 30 years, Digital Geometry in Image Processing presents a mathematical treatment of the properties of digital metric spaces and their relevance in analyzing shapes in two and three dimensions. Unlike similar books, this one connects the two areas of image processing and digital geometry, highlighting important results of digital geometry that are currently used in image analysis and processing.The book discusses different digital geometries in multi-dimensional integral coordinate spaces. It also describes interesting properties of the geometries, including metric and topological properties, shapes of circles and spheres, proximity to Euclidean norms, and number theoretic representations of geometric objects such as straight lines and circles. The authors—all active researchers in image processing and digital geometry—demonstrate how these concepts and properties are useful in various techniques for image processing and analysis. In particular, the book covers applications in object representation and shape analysis.With many figures (some in color) and end-of-chapter exercises, this book provides an in-depth, unified account of digital metrics, the characterization of digital curves and straight lines, and their uses in shape analysis. It gives you insight on the latest two- and three-dimensional image processing applications.

The textbook is primarily written for senior undergraduate and post graduate students studying in areas of computer science and engineering, and electrical engineering. However, as the subject covers various interdisciplinary areas, the book is also expected to be of interest to a larger readership in Science and Engineering. It has a comprehensive and balanced coverage of theory and applications of computer vision with a textbook approach providing worked out examples, and exercises. It covers theory and applications of some relatively recent advancements in technology such as on colour processing, deep learning techniques for processing images and videos, document processing, biometry, content based image retrieval, etc. It also delves with theories and processing in non-optical imaging systems, such as range or depth imaging, medical imaging and remote sensing imaging.

As more images and videos are becoming available in compressed formats, researchers have begun designing algorithms for different image operations directly in their domains of representation, leading to faster computation and lower buffer requirements. Image and Video Processing in the Compressed Domain presents the fundamentals, properties, and applications of a variety of image transforms used in image and video compression. It illustrates the development of algorithms for processing images and videos in the compressed domain.Developing concepts from first principles, the book introduces popular image and video compression algorithms, in particular JPEG, JPEG2000, MPEG-2, MPEG-4, and H.264 standards. It also explores compressed domain analysis and performance metrics for comparing algorithms. The author then elucidates the definitions and properties of the discrete Fourier transform (DFT), discrete cosine transform (DCT), integer cosine transform (ICT), and discrete wavelet transform (DWT). In the subsequent chapters, the author discusses core operations, such as image filtering, color enhancement, image resizing, and transcoding of images and videos, that are used in various image and video analysis approaches. He also focuses on other facets of compressed domain analysis, including video editing operations, video indexing, and image and video steganography and watermarking.With MATLAB® codes available as a download from the CRC Press website, this book takes you through the steps involved in processing and analyzing compressed videos and images. It covers the algorithms, standards, and techniques used for coding images and videos in compressed formats.

As more images and videos are becoming available in compressed formats, researchers have begun designing algorithms for different image operations directly in their domains of representation, leading to faster computation and lower buffer requirements. Image and Video Processing in the Compressed Domain presents the fundamentals, properties, and applications of a variety of image transforms used in image and video compression. It illustrates the development of algorithms for processing images and videos in the compressed domain.Developing concepts from first principles, the book introduces popular image and video compression algorithms, in particular JPEG, JPEG2000, MPEG-2, MPEG-4, and H.264 standards. It also explores compressed domain analysis and performance metrics for comparing algorithms. The author then elucidates the definitions and properties of the discrete Fourier transform (DFT), discrete cosine transform (DCT), integer cosine transform (ICT), and discrete wavelet transform (DWT). In the subsequent chapters, the author discusses core operations, such as image filtering, color enhancement, image resizing, and transcoding of images and videos, that are used in various image and video analysis approaches. He also focuses on other facets of compressed domain analysis, including video editing operations, video indexing, and image and video steganography and watermarking.With MATLAB® codes on an accompanying CD-ROM, this book takes you through the steps involved in processing and analyzing compressed videos and images. It covers the algorithms, standards, and techniques used for coding images and videos in compressed formats.

Exploring theories and applications developed during the last 30 years, Digital Geometry in Image Processing presents a mathematical treatment of the properties of digital metric spaces and their relevance in analyzing shapes in two and three dimensions. Unlike similar books, this one connects the two areas of image processing and digital geometry, highlighting important results of digital geometry that are currently used in image analysis and processing.The book discusses different digital geometries in multi-dimensional integral coordinate spaces. It also describes interesting properties of the geometries, including metric and topological properties, shapes of circles and spheres, proximity to Euclidean norms, and number theoretic representations of geometric objects such as straight lines and circles. The authors—all active researchers in image processing and digital geometry—demonstrate how these concepts and properties are useful in various techniques for image processing and analysis. In particular, the book covers applications in object representation and shape analysis.With many figures (some in color) and end-of-chapter exercises, this book provides an in-depth, unified account of digital metrics, the characterization of digital curves and straight lines, and their uses in shape analysis. It gives you insight on the latest two- and three-dimensional image processing applications.

This book describes various new computer based approaches which can be exploited for the (digital) reconstruction, recognition, restoration, presentation and classification of digital heritage. They are based on applications of virtual reality, augmented reality and artificial intelligence, to be used for storing and retrieving of historical artifacts, digital reconstruction, or virtual viewing.The book is divided into three sections: “Classification of Heritage Data” presents chapters covering various domains and aspects including text categorization, image retrieval and classification, and object spotting in historical documents. Next, in “Detection and Recognition of Digital Heritage Artifacts”, techniques like neural networks or deep learning are used for the restoration of degraded heritage documents, Tamil Palm Leaf Characters recognition, the reconstruction of heritage images, and the selection of suitable images for 3D reconstruction and classification of Indian land mark heritage images. Lastly, “Applications of Modern Tools in Digital Heritage” highlights some example applications for dance transcription, architectural geometry of early temples by digital reconstruction, and computer vision based techniques for collecting and integrating knowledge on flora.This book is mainly written for researchers and graduate students in digital preservation and heritage, or computer scientists looking for applications of virtual reality, computer vision, and artificial intelligence techniques.

This book describes various new computer based approaches which can be exploited for the (digital) reconstruction, recognition, restoration, presentation and classification of digital heritage. They are based on applications of virtual reality, augmented reality and artificial intelligence, to be used for storing and retrieving of historical artifacts, digital reconstruction, or virtual viewing.The book is divided into three sections: “Classification of Heritage Data” presents chapters covering various domains and aspects including text categorization, image retrieval and classification, and object spotting in historical documents. Next, in “Detection and Recognition of Digital Heritage Artifacts”, techniques like neural networks or deep learning are used for the restoration of degraded heritage documents, Tamil Palm Leaf Characters recognition, the reconstruction of heritage images, and the selection of suitable images for 3D reconstruction and classification of Indian land mark heritage images. Lastly, “Applications of Modern Tools in Digital Heritage” highlights some example applications for dance transcription, architectural geometry of early temples by digital reconstruction, and computer vision based techniques for collecting and integrating knowledge on flora.This book is mainly written for researchers and graduate students in digital preservation and heritage, or computer scientists looking for applications of virtual reality, computer vision, and artificial intelligence techniques.

This edited volume contains a selection of refereed and revised papers originally presented at the International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2014), March 13-15, 2014, Trivandrum, India. The program committee received 134 submissions from 11 countries. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 52 papers were finally selected. The papers offer stimulating insights into Pattern Recognition, Machine Learning and Knowledge-Based Systems; Signal and Speech Processing; Image and Video Processing; Mobile Computing and Applications and Computer Vision. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas.

This book constitutes the thoroughly refereed post-conference proceedings of the third International Symposium on Intelligent Systems Technologies and Applications (ISTA’17), September 13-16, 2017, Manipal, Karnataka, India. All submissions were evaluated on the basis of their significance, novelty, and technical quality. This proceedings contains 34 papers selected for presentation at the Symposium.

This book explores and discusses various aspects of intelligent systems technologies and their applications. It constitutes the thoroughly refereed post-conference proceedings of the 4th International Symposium on Intelligent Systems Technologies and Applications (ISTA’18), September 19-22, 2018, Bangalore, India. All submissions were evaluated on the basis of their significance, novelty, and technical quality. This book contains 20 papers selected for presentation at the Symposium. The book is chiefly intended for, and offers a valuable resource for, researchers and scientists engaged in various fields involving intelligent systems.

This book constitutes the refereed proceedings of the 5th International Symposium on Advances in Signal Processing and Intelligent Recognition Systems, SIRS 2019, held in Trivandrum, India, in December 2019. The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 63 submissions.

This book discusses different types of distance functions defined in an n-D integral space for their usefulness in approximating the Euclidean metric. It discusses the properties of these distance functions and presents various kinds of error analysis in approximating Euclidean metrics.

This book constitutes thoroughly refereed post-conference proceedings of the 7th International Symposium on Intelligent Informatics (ISI 2022), from August 31 to September 1–2, 2022, Trivandrum, India.