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Computational Morphology

Author: G.T. Toussaint
Publisher: Elsevier
ISBN: 1483296725
Size: 77.28 MB
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Computational Geometry is a new discipline of computer science that deals with the design and analysis of algorithms for solving geometric problems. There are many areas of study in different disciplines which, while being of a geometric nature, have as their main component the extraction of a description of the shape or form of the input data. This notion is more imprecise and subjective than pure geometry. Such fields include cluster analysis in statistics, computer vision and pattern recognition, and the measurement of form and form-change in such areas as stereology and developmental biology. This volume is concerned with a new approach to the study of shape and form in these areas. Computational morphology is thus concerned with the treatment of morphology from the computational geometry point of view. This point of view is more formal, elegant, procedure-oriented, and clear than many previous approaches to the problem and often yields algorithms that are easier to program and have lower complexity.

Visual Form

Author: C. Arcelli
Publisher: Springer Science & Business Media
ISBN: 1489907157
Size: 71.67 MB
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This book contains the papers presented at the International Workshop on Visual Fonn, held in Capri (Italy) on May 27-30, 1991. The workshop, sponsored by the International Association for Pattern Recognition (!APR), has been jointly organized by the Dipartimento di Infonnatica e Sisternistica of the University of Naples and the Istituto di Cibemetica of the National Research Council of Italy, and has focussed on Shape. Shape is a distinctive feature of most patterns, so that recognition can often be attained through shape discrimination. The organizers of the workshop shared the general feeling manifested by researchers, that it was time for holding a meeting exclusively devoted to a feature so crucial for both human and machine perception. During this meeting, problems and prospects in the field of 2D and 3D shape analysis could be discussed extensively, so as to provide an effective, updated picture of the current research activity in which shape plays a central role. Indeed, many highly qualified researchers in the field positively reacted to the Call for Papers.

Report Cs R

Author: Centrum voor Wiskunde en Informatica (Amsterdam, Netherlands) Dept. of Computer Science
Size: 47.52 MB
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Finding Color And Shape Patterns In Images

Author: Scott Cohen
Size: 48.43 MB
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Abstract: "This thesis is devoted to the Earth Mover's Distance (EMD), an edit distance between distributions, and its use within content-based image retrieval (CBIR). The major CBIR problem discussed is the pattern problem: Given an image and a query pattern, determine if the image contains a region which is visually similar to the pattern; if so, find at least one such image region. An important problem that arises in applying the EMD to CBIR is the EMD under transformation (EMDG̲) problem: find a transformation of one distribution which minimizes its EMD to another, where the set of allowable transformations G is given. The problem of estimating the size/scale at which a pattern occurs in an image is phrased and efficiently solved as an EMDG̲ problem. For a large class of transformation sets, we also present a monotonically convergent iteration to find at least a locally optimal transformation. Our pattern problem solution is the SEDL (Scale Estimation for Directed Location) image retrieval system. Three important contributions of SEDL are (1) a general framework for finding both color and shape patterns, (2) the previously mentioned scale estimation algorithm using the EMD, and (3) a directed (as opposed to exhaustive) search strategy."

Soft Computing Approach To Pattern Recognition And Image Processing

Author: Ashish Ghosh
Publisher: World Scientific
ISBN: 9789812776235
Size: 53.49 MB
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This volume provides a collection of sixteen articles containing review and new material. In a unified way, they describe the recent development of theories and methodologies in pattern recognition, image processing and vision using fuzzy logic, artificial neural networks, genetic algorithms, rough sets and wavelets with significant real life applications. The book details the theory of granular computing and the role of a rough-neuro approach as a way of computing with words and designing intelligent recognition systems. It also demonstrates applications of the soft computing paradigm to case based reasoning, data mining and bio-informatics with a scope for future research. The contributors from around the world present a balanced mixture of current theory, algorithms and applications, making the book an extremely useful resource for students and researchers alike. Contents: Pattern Recognition: Multiple Classifier Systems; Building Decision Trees from the Fourier Spectrum of a Tree Ensemble; Clustering Large Data Sets; Multi-objective Variable String Genetic Classifier: Application to Remote Sensing Imagery; Image Processing and Vision: Dissimilarity Measures Between Fuzzy Sets or Fuzzy Structures; Early Vision: Concepts and Algorithms; Self-organizing Neural Network for Multi-level Image Segmentation; Geometric Transformation by Moment Method with Wavelet Matrix; New Computationally Efficient Algorithms for Video Coding; Soft Computing for Computational Media Aesthetics: Analyzing Video Content for Meaning; Granular Computing and Case Based Reasoning: Towards Granular Multi-agent Systems; Granular Computing and Pattern Recognition; Case Base Maintenance: A Soft Computing Perspective; Real Life Applications: Autoassociative Neural Network Models for Pattern Recognition Tasks in Speech and Image; Protein Structure Prediction Using Soft Computing; Pattern Classification for Biological Data Mining. Readership: Upper level undergraduates, graduates, researchers, academics and industrialists.

Computer Vision

Author: Richard Szeliski
Publisher: Springer Science & Business Media
ISBN: 9781848829350
Size: 56.45 MB
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Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.