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Title Automatic diatom identification / editors, Hans du Buf, Micha M. Bayer.
Imprint River Edge, N.J. : World Scientific, ©2002.

Series Series in machine perception and artificial intelligence ; v. 51
Series in machine perception and artificial intelligence ; v. 51.
Subject Diatoms -- Identification -- Data processing.
Pattern recognition systems.
Alt Name Du Buf, Hans.
Bayer, Micha M.
Description 1 online resource (xi, 316 pages) : illustrations
Bibliography Note Includes bibliographical references.
Note Print version record.
Contents 1. Introduction to ADIAC and this book / Hans du Buf and Micha M. Bayer -- 2. Diatoms: organism and image / David G. Mann -- 3. Diatom applications / Richard J. Telford [and others] -- 4. ADIAC imaging techniques and databases / Micha M. Bayer and Steve Juggins -- 5. Human error and quality assurance in diatom analysis / Martyn G. Kelly [and others] -- 6. Contour extraction / Stefan Fischer, Hamid R. Shahbazkia, and Horst Bunke -- 7. Identification using classical and new features in combination with decision tree ensembles / Stefan Fischer and Horst Bunke -- 8. Identification by curvature of convex and concave segments / Robert E. Loke and Hans du Buf -- 9. Identification by contour profiling and legendre polynomials / Adrian Ciobanu and Hans du Buf -- 10. Identification by Gabor features / Luis M. Santos and Hans du Buf -- 11. Identification by mathematical morphology / Michael H.F. Wilkinson [and others] -- 12. Mixed-method identifications / Michel A. Westenberg and Jos B.T.M. Roerdink -- 13. Automatic slide scanning / Jose L. Pech-Pacheco and Gabriel Cristobal -- 14. ADIAC achievements and future work / Hans du Buf and Micha M. Bayer.
Summary This is the first book to deal with automatic diatom identification. It provides the necessary background information concerning diatom research, useful for both diatomists and non-diatomists. It deals with the development of electronic databases, image preprocessing, automatic contour extraction, the application of existing contour and ornamentation features and the development of new ones, as well as the application of different classifiers (neural networks, decision trees, etc.). These are tested using two image sets: (i) a very difficult set of Sellaphora pupula with 6 demes and 120 images; (ii) a mixed genera set with 37 taxa and approximately 800 images. The results are excellent, and recognition rates well above 90% have been achieved on both sets. The results are compared with identification rates obtained by human experts. One chapter of the book deals with automatic image capture, i.e. microscope slide scanning at different resolutions using a motorized microscope stage, autofocusing, multifocus fusion, and particle screening to select only diatoms and to reject debris. This book is the final scientific report of the European ADIAC project (Automatic Diatom Identification and Classification), and it lists the web-sites with the created public databases and an identification demo.
ISBN 9812777865 (electronic bk.)
9789812777867 (electronic bk.)
OCLC # 305128383
Additional Format Print version: Automatic diatom identification. River Edge, NJ : World Scientific, ©2002 9810248865 9789810248864 (DLC) 2005274892 (OCoLC)50633000

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