Practical algorithms for image analysis: description, examples, and code by Lawrence O'Gorman, Michael J. Sammon, Michael Seul

Practical algorithms for image analysis: description, examples, and code



Practical algorithms for image analysis: description, examples, and code epub




Practical algorithms for image analysis: description, examples, and code Lawrence O'Gorman, Michael J. Sammon, Michael Seul ebook
Format: djvu
Page: 299
ISBN: 0521660653, 9780521660655
Publisher: Cambridge University Press


Topics: Digitization, processing, segmentation, projection, data structures, binary images, contour filling, thinning, curve fitting, surface fitting, 2-D graphics, polygon clipping, 3-D graphics. And now the accompanying CD-ROM contains C programs not only as source code for carrying out the book's procedures but also as executables with a graphical user interface for Windows and Linux. In no way we impose here the method of resolution on the Reader and we only provide the confirmation of a possibility of its practical implementation. Nonetheless, it is great to have The book also contains necessary information about basic standard libraries responsible for xml processing or web pages downloading. Colophon Some code samples are actually incorrect implementations of the given algorithm and there are antipatterns like string sql concatenation in the code without a warning comment to the reader to remind them it's a bad practice. Blog Entry, Practical Algorithms for Image Analysis: Descriptions, Examples, and Code (Hardcover), Dec 25, '07 9:28 AM for everyone. Each self-contained section projects for classroom use. The book has basic algorithms for many standard image processing tasks. The results The presented source code is shown only in the form of example of implementable selected algorithm. How bioinformatics influences health informatics: usage of biomolecular sequences, expression profiles and automated microscopic image analyses for clinical needs and public health . The monograph comprises proposals of new and also of known algorithms, modified by authors, for image analysis and processing, presented on the basis of example of Matlab environment with Image Processing tools. Drawing on their long experience as users and developers of image analysis algorithms and software, the authors present a description and implementation of the most suitable procedures in easy-to-use form.