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Series in Machine Perception and Artificial Intelligence - Vol. 51
AUTOMATIC DIATOM IDENTIFICATION
edited by Hans du Buf (University of Algarve, Portugal) & Micha M Bayer (Royal Botanic Garden, Edinburg, UK)
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.
Contents:
- Introduction to ADIAC and This Book (H Du Buf & M M Bayer)
- Diatoms:
Organism and Image (D G Mann)
- Diatom Applications (R J Telford et al.)
- ADIAC Imaging Techniques and Databases (M M Bayer & S Juggins)
- Human Error and Quality Assurance in Diatom Analysis (M G Kelly et al.)
- Contour Extraction (S Fischer et al.)
- Identification Using Classical and New Features in Combination with Decision Tree Ensembles (S Fischer & H Bunke)
- Identification by Curvature of Convex and Concave Segments (R E Loke & H du Buf)
- Identification by Contour Profiling and Legendre Polynomials (A Ciobanu & H du Buf)
- Identification by Gabor Features (L M Santos & H du Buf)
- Identification by Mathematical Morphology (M H F Wilkinson et al.)
- Mixed-Method Identifications (M A Westenberg & J B T M Roerdink)
- Automatic Slide Scanning (J L Pech-Pacheco & G Cristóbal)
- ADIAC Achievements and Future Work (H du Buf & M M Bayer)
Readership: Researchers in pattern recognition and computer vision,
researchers working with diatoms, and psychologists.
| 328pp |
Pub. date: Jul 2002 |
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