Automatic Diatom Identification

By: Micha M Bayer (Editor), Hans Du Buf (Editor)

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Hardcover | 15 July 2002

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Hardcover
328 Pages

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24.77 x 17.15 x 2.54

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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 percent 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.

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You Can Find This Book In

Non-Fiction Engineering & Technology Electronics & Communications Engineering Electronics Engineering Automatic Control Engineering Computing & I.T.Computer Science Artificial Intelligence Computer Vision Science Biology, Life Sciences Hydrobiology

Marine Biology Microbiology excluding Medical Botany & Plant Sciences Phycology, Algae & Lichens Booktopia Publisher Services World Scientific Publishing

Preface
Acknowledgments
Authors' Affiliations
Introduction to ADIAC and This Book	p. 1
Diatoms: Organism and Image	p. 9
Diatom Applications	p. 41
ADIAC Imaging Techniques and Databases	p. 55
Human Error and Quality Assurance in Diatom Analysis	p. 75
Contour Extraction	p. 93
Identification Using Classical and New Features in Combination with Decision Tree Ensembles	p. 109
Identification by Curvature of Convex and Concave Segments	p. 141
Identification by Contour Profiling and Legendre Polynomials	p. 167
Identification by Gabor Features	p. 187
Identification by Mathematical Morphology	p. 221
Mixed-Method Identifications	p. 245
Automatic Slide Scanning	p. 259
ADIAC Achievements and Future Work	p. 289
The Mixed Genera Data Set	p. 299
Table of Contents provided by Blackwell. All Rights Reserved.

Automatic Diatom Identification

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Hardcover

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