Last edited by Shaktilmaran
Wednesday, May 6, 2020 | History

4 edition of Image representation and processing found in the catalog.

Image representation and processing

a recursive approach

by V. V. Aleksandrov

  • 249 Want to read
  • 26 Currently reading

Published by Kluwer Academic Publishers in Dordrecht, Boston .
Written in English

    Subjects:
  • Image processing.,
  • Image processing -- Mathematical models.

  • Edition Notes

    Includes bibliographical references (p. 177-186) and index.

    Statementby V.V. Alexandrov and N.D. Gorsky.
    SeriesMathematics and its applications ;, v. 261, Mathematics and its applications (Kluwer Academic Publishers) ;, v. 261.
    ContributionsGorskiĭ, N. D.
    Classifications
    LC ClassificationsTA1637 .A44 1993
    The Physical Object
    Paginationviii, 191 p. :
    Number of Pages191
    ID Numbers
    Open LibraryOL1410913M
    ISBN 100792321367
    LC Control Number93019677

    Chapter 8 Image Representation and Description CHAPTER OBJECTIVES To discuss the various representation and description schemes. To address the role of chain codes in representing the boundary of an image - Selection from Fundamentals of Digital Image Processing [Book]. digital image processing is an extensive set of functions for processing mul- remainder of the book. Digital Image Representation. An image may be defined as a two-dimensional function. fx (,y), where. x. and. y. In many image processing books, the image origin is defined to be at (, xy)File Size: 1MB.

    Binary Digital Image Processing is aimed at faculty, postgraduate students and industry specialists. It is both a text reference and a textbook that reviews and analyses the research output in this field of binary image processing. It is aimed at both advanced researchers as well as educating the novice to this area. Summary. Covering the theoretical aspects of image processing and analysis through the use of graphs in the representation and analysis of objects, Image Processing and Analysis with Graphs: Theory and Practice also demonstrates how these concepts are indispensible for the design of cutting-edge solutions for real-world applications. Explores new applications in computational photography.

      Types of an image. BINARY IMAGE– The binary image as its name suggests, contain only two pixel elements i.e 0 & 1,where 0 refers to black and 1 refers to image is also known as Monochrome. BLACK AND WHITE IMAGE– The image which consist of only black and white color is called BLACK AND WHITE IMAGE.; 8 bit COLOR FORMAT– It is the most famous image /5.   Image representation & description 1. DIGITAL IMAGE PROCESSINGREPRESENTATION & DESCRIPTION by Paresh Kamble 2. Introduction• After an image is segmented into regions; the resulting aggregate of segmented pixels is represented & described for further computer processing.•.


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Image representation and processing by V. V. Aleksandrov Download PDF EPUB FB2

Image Representation and Processing: A Recursive Approach (Mathematics And Its Applications (Closed)) [V.V. Alexandrov] on *FREE* shipping on qualifying offers.

Recently, much attention has been paid to image processing with multiresolution and hierarchical structures such as pyramids and trees. This volume deals with recursive pyramids. The major aspects of this book are two original mathematical models of greyscale and binary images represented by recursive structures.

Image compression, transmission and processing are discussed using these models. Visual Information Representation, Communication, and Image Processing (Optical Science and Engineering) 1st Edition by Ya-Qin Zhang (Editor).

This new book is suitable for audiences in interdisciplinary areas with applications of image processing. Steven Tanimoto uses an intuitive and efficient structure to describe image processing topics, and offers many illustrations using PixelMath, a unique image processing by: 4.

Chapter 2 Digital Image Representation CHAPTER OBJECTIVES To illustrate how to represent the image in a computer. To describe the image representation in 2D.

To explore the use of sampling - Selection from Fundamentals of Digital Image Processing [Book]. The primary textbook in its space for larger than twenty years, it continues its slicing-edge give consideration to trendy developments in all mainstream areas of image processing—e.g., image fundamentals, image enhancement inside the spatial and frequency domains, restoration, color image processing, wavelets, image compression, morphology.

(11) Representation and Description - Low-level image processing Æ Image enhancement, restoration, transformation - Mid-level image processing (image understanding) Æ Object representation, description Image Segmentation Object Representation/ Description Restored/ Transformed Image Segmented Image Representation/ Description/ Features ImageFile Size: 95KB.

Image Representation and Description Shahram Ebadollahi DIP ELEN E 4/15/ 2 Image Description Recognition High-level Image Representation Image representation and processing book Understanding.

4/15/ 3 Lecture Outline Image Description Shape Descriptors Texture & Texture Descriptors SIFT Motion Descriptors. Image as a functionII The fact that a 2-D image is aprojectionof a 3-D function is very important in some applications.

(From Schmidt, Mohr and Bauckhage, IJCV, ) This in important in image stitching, for example, where the structure of the projection can be used to constrain the image transformation from different view points.

Chapter 2 Imaging and Image Represen tation Humans deriv e a great deal of information ab out the w orld through their visual sense. Ligh t re ects o ob jects and sometimes passes through ob jects to create an image on the retina of eac hey e.

F rom this pair of images m uc h of the structure of the 3D en vironmen t is de-rivFile Size: KB. This book is a collection of topics dealing with new concepts, techniques, applications, and standards relating the area of visual presentation and communications. The editors have invited a host of world authorities to address several special topics of great importance.

Gonzalez is author or co-author of over technical articles, two edited books, and four textbooks in the fields of pattern recognition, image processing and robotics. His books are used in over universities and research institutions throughout the world.4/5(53).

xvi Preface Expansion of the coverage on image segmentation to include more ad- vanced edge detection techniques such as Canny’s algorithm, and a more comprehensive treatment of image thresholding.

An update of the chapter dealing with image representation and description. Streamlining the material dealing with structural object Size: 2MB. Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology Methods and Algorithms, Proceedings of IC3DITVolume 1 Series: Smart Innovation, Systems and Technologies, Vol.

The Journal of Visual Communication and Image Representation publishes papers on state-of-the-art visual communication and image representation, with emphasis on novel technologies and theoretical work in this multidisciplinary area of pure and applied research.

The field of visual communication and image representation is considered in its broadest sense and covers both digital and analog. Book Chapters (additional chapters in Book Chapters) Pedro M. Aguiar, Radu Jasinschi, José M.

Moura, and Charnchai Pluempitiwiriyawej, "Content-based Image Sequence Representation," ed. Todd Reed, in Digital Image Sequence Processing: Compression and Analysis, CRC Press Handbook, in press, (61 pages).

Invited Chapter. A wavelet image representation can be thought of as a tree-structured spatial set of coefficients. A wavelet coefficient tree is defined as the set of coefficients from different bands that represent the same spatial region in the image.

Figure shows a three-level wavelet decomposition of the Lena image, together with a wavelet coefficient tree structure representing the eye region of Lena. Meant for students and practicing engineers, this book provides a clear, comprehensive and up-to-date introduction to Digital Image Processing in a pragmatic style.

An illustrative approach, practical examples and MATLAB applications given in the book help in bringing the theory to life.4/5(13). Chapter 1: Introduction 2 Text book Textbook: Rafael C. Gonzalez and Richard E.

Woods, "Digital Image Processing, 3 rd edition", Prentice Hall. Digital Image Processing. 3 Course Content Representation &Segmentation Chapter 11 Representation &Segmentation Chapter 12 Object RecognitionFile Size: 1MB. This book provides a comprehensive view of the topic of sparse and redundant representation modeling, and its use in signal and image processing.

It offers a systematic and ordered exposure to the theoretical foundations of this data model, the numerical aspects of the involved algorithms, and the signal and image processing applications that benefit from these advancements/5(6). Summary: Deals with recursive pyramids, which combine the advantages of available multiresolution structures and which are convenient for both global and local image processing.

The major aspects of the book are two mathematical models of greyscale and binary images represented ."Digital Image Processing Using MATLAB" is the first book that provides a balanced treatment of image processing fundamentals and the software principles used in their practical implementation.

The book integrates material from the leading text, "Digital Image Processing" by Gonzalez and Woods, and the Image Processing Toolbox of the MathWorks.5/5(4).38 Chapter 2 Digital Image Fundamentals 15 m C m 17 mm FIGURE Graphical representation of the eye looking at a palm tree.

Point C is the optical center of the lens. focuses on an object farther away than about 3 m,the lens exhibits its lowest re-fractive the eye focuses on a nearby object,the lens is most strong-File Size: KB.