This book solves a long-standing problem in computer vision, the interpretation of line drawings and, in doing so answers many of the concerns raised by this problem, particularly with regard to errors in the placement of lines and vertices in the images. Sugihara presents a computational mechanism that functionally mimics human perception in being able to generate three-dimensional descriptions of objects from two-dimensional line drawings. The objects considered are polyhedrons or solid objects bounded by planar faces, and the line drawings are single-view pictures of these objects. Sugihara's mechanism has several potential applications. It can facilitate man-machine communication by extracting object structures automatically from pictures drawn by a designer, which can be particularly useful in the computer-aided design of geometric objects, such as mechanical parts and buildings. It can also be used in the intermediate stage of computer vision systems used to obtain and analyze images in the outside world. The computational mechanism itself is not accompanied by a large database but is composed of several simple procedures based on linear algebra and combinatorial theory. Contents:Introduction. Candidates for Spatial Interpretation. Discrimination between Correct and Incorrect Pictures. Correctness of HiddenPart-Drawn Pictures. Algebraic Structures of Line Drawings. Combinatorial Structures of Line Drawings. Overcoming Superstrictness. Algorithmic Aspects of Generic Reconstructibility. Specification of Unique Shapes. Recovery of Shape from Surface Information. Polyhedrons and Rigidity. Kokichi Sugihara is Professor in the Department of Mathematical Engineering and instrumentation Physics, Faculty of Engineering, the University of Tokyo, Tokyo, Japan. Machine interpretation of Line Drawingsis included in The MIT Press Series in Artificial Intelligence, edited by Patrick Henry Winston and Michael Brady.

Line drawing interpretation is a challenging area with enormous practical potential. At present, many companies throughout the world invest large amounts of money and human resource in the input of paper drawings into computers. The technology needed to produce an image of a drawing is widely available, but the transformation of these images into more useful forms is an active field of research and development. Machine Interpretation of Line Drawing Images - describes the theory and practice underlying the computer interpretation of line drawing images and - shows how line drawing interpretation systems can be developed. The authors show how many of the problems can be tackled and provide a thorough overview of the processes underpinning the interpretation of images of line drawings.

Based on the author’s considerable research, this book contains state-of-the-art reviews of work in drawing interpretation and discrete optimization. It covers both drawings of polyhedral objects as well as complex curved objects.

About the Book: Written by three distinguished authors with ample academic and teaching experience, this textbook, meant for diploma and degree students of Mechanical Engineering as well as those preparing for AMIE examination, incorporates the latest st

Recognition and learning by a computer. Representing information. Generation and transformation of representations. Pattern feature extraction. Pattern understanding methods. Learning concepts. Learning procedures. Learning based on logic. Learning by classification and discovery. Learning by neural networks.

This unique book discusses machine understanding (MU). This new branch of classic machine perception research focuses on perception that leads to understanding and is based on the categories of sensory objects. In this approach the visual and non-visual knowledge, in the form of visual and non-visual concepts, is used in the complex reasoning process that leads to understanding. The book presents selected new concepts, such as perceptual transformations, within the machine understanding framework, and uses perceptual transformations to solve perceptual problems (visual intelligence tests) during understanding, where understanding is regarded as an ability to solve complex visual problems described in the authors’ previous books. Thanks to the uniqueness of the research topics covered, the book appeals to researchers from a wide range of disciplines, especially computer science, cognitive science and philosophy.

The Manual of Engineering Drawing has long been recognised as the student and practising engineer's guide to producing engineering drawings that comply with ISO and British Standards. The information in this book is equally applicable to any CAD application or manual drawing. The second edition is fully in line with the requirements of the new British Standard BS8888: 2002, and will help engineers, lecturers and students with the transition to the new standards.BS8888 is fully based on the relevant ISO standards, so this book is also ideal for an international readership. The comprehensive scope of this book encompasses topics including orthographic, isometric and oblique projections, electric and hydraulic diagrams, welding and adhesive symbols, and guidance on tolerancing.Written by a member of the ISO committee and a former college lecturer, the Manual of Engineering Drawing combines up-to-the-minute technical accuracy with clear, readable explanations and numerous diagrams. This approach makes this an ideal student text for vocational courses in engineering drawing and undergraduates studying engineering design / product design.Colin Simmons is a member of the BSI and ISO Draughting Committees and an Engineering Standards Consultant. He was formerly Standards Engineer at Lucas CAV.* Fully in line with the latest ISO Standards* A textbook and reference guide for students and engineers involved in design engineering and product design* Written by a former lecturer and a current member of the relevant standards committees

This book describes experimental advances made in the interpretation of visual motion over the last few years that have moved researchers closer to emulating the way in which we recover information about the surrounding world.

A study of multispectral image processing and pattern recognition. It covers: geometric and orthogonal moments; minimum description length method for facet matching; an integrated vision system for ALV navigation; fuzzy Bayesian networks; and more.