Image processing and computer vision are currently hot topics with undergraduates and professionals alike. "Feature Extraction and Image Processing" provides an essential guide to the implementation of image processing and computer vision techniques, explaining techniques and fundamentals in a clear and concise manner. Readers can develop working techniques, with usable code provided throughout and working Matlab and Mathcad files on the web. Focusing on feature extraction while also covering issues and techniques such as image acquisition, sampling theory, point operations and low-level feature extraction, the authors have a clear and coherent approach that will appeal to a wide range of students and professionals.The new edition includes: a new coverage of curvature in low-level feature extraction (SIFT and saliency) and features (phase congruency); geometric active contours; morphology; and camera models and an updated coverage of image smoothing (anistropic diffusion); skeletonization; edge detection; curvature; and shape descriptions (moments). It is an essential reading for engineers and students working in this cutting edge field. It is an ideal module text and background reference for courses in image processing and computer vision. It features a companion website that includes worksheets, links to free software, Matlab files, solutions and new demonstrations.

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Feature Extraction and Image Processing

This revised and expanded new edition of an internationally successful classic presents an accessible introduction to the key methods in digital image processing for both practitioners and teachers. Emphasis is placed on practical application, presenting precise algorithmic descriptions in an unusually high level of detail, while highlighting direct connections between the mathematical foundations and concrete implementation. The text is supported by practical examples and carefully constructed chapter-ending exercises drawn from the authors' years of teaching experience, including easily adaptable Java code and completely worked out examples. Source code, test images and additional instructor materials are also provided at an associated website. Digital Image Processingis the definitive textbook for students, researchers, and professionals in search of critical analysis and modern implementations of the most important algorithms in the field, and is also eminently suitable for self-study.

Digital Image Processing: An Algorithmic Introduction Using Java

An apparatus and method for real-time volume processing and universal three-dimensional rendering. The apparatus includes a plurality of three-dimensional (3D) memory units (24); at least one pixel bus for providing global horizontal communication (34); a plurality of rendering pipelines; at least one geometry bus (46); and a control unit (38). The apparatus includes a block processor having a circular ray integration pipeline for processing voxel data and ray data. Rays are generally processed in image order thus permitting great flexibility (e.g., perspective projection, global illumination). The block processor includes a splatting unit and a scattering unit. A method for casting shadows and performing global illumination in relation to light sources, which includes sweeping a two dimensional array of rays through the volume, can also be implemented with the apparatus. A method for approximating a perspective projection includes using parallel projection.

Apparatus and method for volume processing and rendering

Many important planning decisions in society and business depend on proper knowledge and a correct understanding of movement, be it in transportation, logistics, biology, or the life sciences. Today the widespread use of mobile phones and technologies like GPS and RFID provides an immense amount of data on location and movement. What is needed are new methods of visualization and algorithmic data analysis that are tightly integrated and complement each other to allow end-users and analysts to extract useful knowledge from these extremely large data volumes. This is exactly the topic of this book. As the authors show, modern visual analytics techniques are ready to tackle the enormous challenges brought about by movement data, and the technology and software needed to exploit them are available today. The authors start by illustrating the different kinds of data available to describe movement, from individual trajectories of single objects to multiple trajectories of many objects, and then proceed to detail a conceptual framework, which provides the basis for a fundamental understanding of movement data. With this basis, they move on to more practical and technical aspects, focusing on how to transform movement data to make it more useful, and on the infrastructure necessary for performing visual analytics in practice. In so doing they demonstrate that visual analytics of movement data can yield exciting insights into the behavior of moving persons and objects, but can also lead to an understanding of the events that transpire when things move. Throughout the book, they use sample applications from various domains and illustrate the examples with graphical depictions of both the interactive displays and the analysis results. In summary, readers will benefit from this detailed description of the state of the art in visual analytics in various ways. Researchers will appreciate the scientific precision involved, software technologists will find essential information on algorithms and systems, and practitioners will profit from readily accessible examples with detailed illustrations for practical purposes.

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Visual Analytics of Movement

Digital geometry is the study of geometrical properties of subsets of digital images. If the digitization is sufficiently fine-grained, such properties can be regarded as approximations to the corresponding properties of the "real" sets that gave rise, by digitization, to the digital sets; but it is also important to define how the properties can be computed for the digital sets themselves. Questions of particular interest include how images and image subsets are digitized; how geometric properties are defined for digitized sets; the computational complexity of computing them--in particular, whether they can be computed using simple (e.g., local) operations; characterizing image operations that preserve them; and characterizing digital objects that could be the digitizations of real objects that have given geometric properties. Concepts that have been extensively studied include topological properties (connected components, boundaries); curves and surfaces; straightness, curvature, convexity, and elongatedness; distance, extent, length, area, surface area, volume, and moments; shape description, similarity, symmetry, and relative position; shape simplification and skeletonization.

Digital geometry

Circular arcs can be drawn on an incremental display device such as a cathode ray tube, digital plotter, or matrix printer using only sign testing and elementary addition and subtraction. This paper describes methodology for producing dot or step patterns closest to the true circle.

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A linear algorithm for incremental digital display of circular arcs

Lines displayed on devices such as incremental plotters, raster CRT or plasma panel displays, and matrix printers must be approximated by sequences of discrete axial and diagonal unit steps in which successive incremental movements are constrained to the movement pattern of the king piece in a game of chess. Described is a Freeman/Reggiori-like algorithm for generating directly the run lengths of constant direction movement within the step sequence in contrast to generating the sequence in its basic unit step elements. The repetitive loop for generating lengths of alternating runs of solely axial and solely diagonal steps requires only integer addition/subtraction together with a sign test and will be executed at most only half the number of times as the comparable loop used to generate the single unit move sequence one step at a time. The algorithm also can be used to examine repetitive patterns and cycles which occur in rastered lines.

Run Length Slice Algorithm for Incremental Lines

In implmenting rater grahic algorithms, it is impotant to toroughly understand behavior and implicit defaults inherent in each algorithm. Design choices must balance performance with respect to drawing speed, circult count, code space, picture fidelity, system complexity, and system consistency. For example, "close" may sound appealing when describing the match of the rastered representation to a geometirc line. An implementation, however, must quantily an error metric?such as minimum normal distance between candidate raster grid points and the geometric line?and resolve "ties" in which two candidate grid points have an equal error metric. Equal error metric ambiguity can permit algorithimic selection of raster points for a line from (X0, Y0) to (X1, Y1) to differ from points selected rastering the same line back from (X1, Y1) to (X0, Y0). Modilying a rastering algorithm to provide an exactly reversibie path, though, will cause problems when lines are rastered in a context of approximating a circle with a polygon. Only by fully understanding any algorithm can designers determine whether such pel-level anomalies are worth the code space or circuit count necessary to provide explicit user resolution, or whether a fixed default must suffice. This article discusses implementation considerations relevant to selecting and customizing incremental line-drawing algorithms to cope with such anomalies as equal error metric instances, perturbation effects of clipping, interesections in raster space, EXOR interpretations for polylines, reversibility, and fractional endpoint rounding.

Ambiguities in Incremental Line Rastering

Raster devices, such as digital plotters, CRT or plasma panel displays, and matrix or ink jet printers, represent 'straight' lines in quantized fashion as a sequence of unit axial and unit diagonal steps. Dichotomons run lengths and periodic repetitive patterns in these incremental or digital lines provide a basis by which the step sequences for quantized lines can be treated in compressed form for storage or transmission. Earnshaw recently published a paper describing an investigation of two compaction alternatives encoding either run lengths or repeated patterns. This paper describes a simple algorithm to incorporate both run length and repeated pattern encoding for step sequence compaction. Also illustrated is the similarity in form of the repetitive loop used to generate either runs or single steps and either full lines or periodic patterns; initial parameter values differ, but the subsequent iterative process is identical.

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Incremental Line Compaction

The invention concerns a graphics display system of the kind having a refresh raster display device, a line clipping mechanism for clipping line primitives for viewing in a selected rectangular viewport having horizontal and vertical edges parallel to the X and Y axes respectively of the display area of the display device, and a vector-to-raster converter for converting the clipped lines to patterns of discrete pels in a refresh buffer, the vector-to-raster converter including an incremental line drawing mechanism responsive to line information supplied by the clipping mechanism to draw the line starting at one endpoint and proceeding towards the other. In such a system, for at least some lines of a kind which have a first endpoint in the viewport and the second endpoint outside the viewport, the clipping mechanism is arranged to avoid calculating the intersection point of the line with the viewport edge intersected by the line, and the vector-to-raster converter is arranged to start the line drawing mechanism at the first endpoint and halt the line drawing mechanism when the currently generated coordinate along the display axis normal th the said viewport edge equals the coordinate of the viewport edge along the same axis.

Jack E. Bresenham

Papers

A linear algorithm for incremental digital display of circular arcs

Run Length Slice Algorithm for Incremental Lines

Ambiguities in Incremental Line Rastering

Incremental Line Compaction

Graphics display system and method having improved clipping technique