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This book constitutes the refereed proceedings of the 14th Scandinavian Conference on Image Analysis, SCIA 2005, held in Joensuu, Finland in June 2005. The 124 papers presented together with 6 invited papers were carefully reviewed and selected from 236 submissions. The papers are organized in topical sections on image segmentation and understanding, color image processing, applications, theory, medical image processing, image compression, digitalization of cultural heritage, computer vision, machine vision, and pattern recognition.
Multicomputers and Image Processing: Algorithms and Programs is the second of a set presenting papers from the third meeting held in Madison, Wisconsin on May 27-30, 1981. The workshop explores the large and powerful multicomputer arrays and networks, with particular emphasis on the related aspects of developing algorithms and programs for multicomputer architectures. Separating 33 papers into chapters, this book reflects the three major aspects of the problem: user algorithms and programs; higher level languages; and multicomputer architectures. The first chapters present specific, larger structure, as well as whole program algorithms and their respective applications. Other chapters describe the important high-level programming of Fortran-based language for the massively parallel processors and the set-theory-based language for expressing the structural image processing and perceptual operations effected by Cytocomputer and other cellular-array-motivated architectures. The concluding chapters examine several major types of computer architectures that are being developed for large parallel-serial multicomputer systems. This book is of great value to computer programmers and scientists.
Evaluation of Multicomputers for Imaging Processing covers the proceedings of the 1984 Tanque Verde Workshop, held in Tucson. This book is organized into four parts encompassing 17 chapters that summarize the benchmark evaluation efforts specific to multicomputer systems designed for the efficient execution of image processing tasks. The first part considers the basic problem of benchmarking and presents an evaluation procedure or sets of instructions for establishing benchmark routines, tasks, and procedures. The next part deals with the simulation and evaluation. This part first examines semiconductor chips designed for use in imaging processing followed by the presentation of formulas for measuring algorithms, architecture efficiency, speedup, and processing element utilization for SIMD/MIMD multicomputers. This part also considers the image processing systems composed of various types of networks of processing elements. The third part describes a content-addressable array and its applications to machine vision, as well as the architecture and programming methods of the WARP multicomputer. This part further looks into the elevation measurements techniques by registering stereo pairs obtained from aerial photography using ""pass point"" correlation methods. The concluding part highlights the hardware implementations of general-purpose image processing systems with associated performance evaluations. Computer scientists and engineers will greatly benefit from this book.
Computer systems that analyze images are critical to a wide variety of applications such as visual inspections systems for various manufacturing processes, remote sensing of the environment from space-borne imaging platforms, and automatic diagnosis from X-rays and other medical imaging sources. Professor Azriel Rosenfeld, the founder of the field of digital image analysis, made fundamental contributions to a wide variety of problems in image processing, pattern recognition and computer vision. Professor Rosenfeld's previous students, postdoctoral scientists, and colleagues illustrate in Foundations of Image Understanding how current research has been influenced by his work as the leading researcher in the area of image analysis for over two decades. Each chapter of Foundations of Image Understanding is written by one of the world's leading experts in his area of specialization, examining digital geometry and topology (early research which laid the foundations for many industrial machine vision systems), edge detection and segmentation (fundamental to systems that analyze complex images of our three-dimensional world), multi-resolution and variable resolution representations for images and maps, parallel algorithms and systems for image analysis, and the importance of human psychophysical studies of vision to the design of computer vision systems. Professor Rosenfeld's chapter briefly discusses topics not covered in the contributed chapters, providing a personal, historical perspective on the development of the field of image understanding. Foundations of Image Understanding is an excellent source of basic material for both graduate students entering the field and established researchers who require a compact source for many of the foundational topics in image analysis.
Describing non-parametric and parametric theoretic classification and the training of discriminant functions, this second edition includes new and expanded sections on neural networks, Fisher's discriminant, wavelet transform, and the method of principal components. It contains discussions on dimensionality reduction and feature selection; novel computer system architectures; proven algorithms for solutions to common roadblocks in data processing; computing models including the Hamming net, the Kohonen self-organizing map, and the Hopfield net; detailed appendices with data sets illustrating key concepts in the text; and more.
Parallel-Algorithms for Regular Architectures is the first book to concentrate exclusively on algorithms and paradigms for programming parallel computers such as the hypercube, mesh, pyramid, and mesh-of-trees.
This book is concerned with the aspects of real-time, parallel computing which are specific to the analysis of digitized images including both the symbolic and semantic data derived from such images. The subjects covered encompass processing, storing, and transmitting images and image data. A variety of techniques and algorithms for the analysis and manipulation of images are explored both theoretically and in terms of implementation in hardware and software. The book is organized into four topic areas: (1) theo retical development, (2) languages for image processing, (3) new computer techniques, and (4) implementation in special purpose real-time digital systems. Computer utilization, methodology, and design for image analy sis presents special and unusual problems. One author (Nagao)* points out that, "Human perception of a scene is very complex. It has not been made clear how perception functions, what one sees in a picture, and how one understands the whole picture. It is almost certain that one carries out a very quick trial-and-error process, starting from the detection of gross prominent features and then analyzing details, using one's knowledge of the world. " Another author (Duff) makes the observation that, "It is therefore more difficult to write computer programs which deal with images than those which deal with numbers, human thinking about arithmetic being a largely conscious activity.
1.1 Background There are many paradigmatic statements in the literature claiming that this is the decade of parallel computation. A great deal of research is being de voted to developing architectures and algorithms for parallel machines with thousands, or even millions, of processors. Such massively parallel computers have been made feasible by advances in VLSI (very large scale integration) technology. In fact, a number of computers having over one thousand pro cessors are commercially available. Furthermore, it is reasonable to expect that as VLSI technology continues to improve, massively parallel computers will become increasingly affordable and common. However, despite the significant progress made in the field, many funda mental issues still remain unresolved. One of the most significant of these is the issue of a general purpose parallel architecture. There is currently a huge variety of parallel architectures that are either being built or proposed. The problem is whether a single parallel computer can perform efficiently on all computing applications.