Practical algorithms for image analysis: description, examples, and code. 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.pdf
ISBN: 0521660653,9780521660655 | 299 pages | 8 Mb


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




Each self-contained section projects for classroom use. Click on image to see enlarged view. How bioinformatics influences health informatics: usage of biomolecular sequences, expression profiles and automated microscopic image analyses for clinical needs and public health . The results The presented source code is shown only in the form of example of implementable selected algorithm. Practical Algorithms for Image Analysis with CD-ROM: Description, Examples, and Code. GO Practical algorithms for image analysis: description, examples, and code. 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. Product Description This book offers guided access to a collection of algorithms for the digital manipulation and analysis of images. Sammon, Michael Seul Type: eBook. Simple color-coding to show code verification results. 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. Author: Lawrence O'Gorman, Michael J. Language: English Released: 2000. PolySpace products use sophisticated math and analysis to prove the absence of run-time errors without the need to compile and run the code. 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. 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.