Project ADIAC: 
Automatic Diatom Identification And Classification

Keywords: phycology, taxonomy, ecology, image processing, pattern recognition, databasing

Note: these pages were under construction until May 2001
You will find similar pages University of Algarve, Portugal.


H du Buf and MM Bayer (eds) (2002). Automatic Diatom Identification. World Scientific, Series in Machine Perception and Artificial Intelligence, Vol 51. 316 pp.

Marking a real milestone in diatom research, this book details all methods and results achieved during ADIAC.

Experience how ADIAC can help you now and in the future: ONLINE DEMO




Summary: The ADIAC project was a pilot study concerning the application of image processing and pattern recognition tools to the automation of diatom identification by computer processing. Instead of using only the shape of the valve outline, we applied several methods to characterize and employ also the valve ornamentation in the identification process. Other important aspects were the development of methods for automatic slide scanning, autofocusing, the realization of big image databases, and  integration into taxonomic/ecological database systems. The project started on May 1 1998 and its duration was three years.

Diatoms have become important in several scientific disciplines not intuitively connected to phycological research. Because of their inert and intricately sculptured shells, and because some have rather narrow ecological preferences, they can be used as ecological indicators. For example, in the study of lake- and sea-bed sediments they can be used to estimate the pH and nutrient status of the water body back in time when the sediments were laid down. They are also  used by archaeologists and forensic scientists to trace ceramic and clothing fragments, and in some cases to establish cause of death. Diatoms are very good indicators of water quality, and authorities responsible for drinking water use them to monitor the quality.

Unfortunately, in many cases  diatom identification is carried out by non-specialists. Furthermore, progress in the use of diatoms in Europe as ecological and palaeoecological indicators, marker fossils, etc., is hampered by the chronic lack of identification tools, inefficient communication, and the slow speed of dealing with samples possibly containing many hundreds of different species. Automation by computer processing and electronic data exchange would help Europe develop the capacity to monitor and respond effectively to change in aquatic systems, and to remain at the forefront of related research.

Towards computer processing

Until recently, diatom research has  always involved identification based on morphological properties. This is tedious work, because microscope slides must be scanned, eventually photographed, and the diatom specimens must be linked to described taxa. The latter is a very complicated task, even for experts, because it requires a profound knowledge of hundreds of genera and thousands of species that often differ very subtly. Information and images are scattered through atlases like those of Schmidt, Tempère, Peragallo and others, and in floras by Hustedt, Krammer & Lange-Bertalot, etc. For these reasons automation by computer processing is of paramount importance, and we are convinced that computer processing will drastically change diatom research in the near future! It is important to remember also that the introduction of DNA bar-coding techniques since 2000 cannot replace morphology-based identification for subfossil and fossil material.

Earlier work on computer identification was always  based on shape descriptors, i.e. parameters which describe the shape of the outline. However, many diatoms cannot be distinguished on shape alone because different species share the same shape, although they may have quite different ornamentations (striae etc) of the valve surface. This was the main emphasis of this ADIAC project: we developed pattern recognition methods to allow identification on the basis of both valve outline and ornamentation.

This multi-disciplinary project, with a duration of three years, brought together researchers from pattern recognition, diatom applications, and taxonomic databases. It must be seen as a bundled European impulse to push diatom research and to make diatom identification an important and challenging subject in the pattern recognition society.

Back to Top


The overall aim of ADIAC was to develop appropriate image databases and analytical methods for the automated identification of diatoms for use in environmental monitoring, micropalaeontology and forensic research etc. The particular objectives were:

1 - To develop diatom image databases with different levels of discrimination complexity. These had to be suitable for testing the methods under study in this project as well as for future research. These databases were to be made accessible to all interested scientists.

2 - To develop methods for scanning slides automatically, i.e. to detect the positions of diatoms and to ignore debris with some complex structure, to store the calibrated positions, and to take high-magnification images at those positions. Autofocusing has to be an integral part of slide scanning, especially at high magnifications.

3 - To develop methods for a complete, graphical, diatom image description, i.e. of both valve shape and ornamentation yet with a limited number of parameters, which allows for a reliable identification.

4 - To develop a diatom identification system based on graph matching that takes all available morphological information into account and that produces a sorted list with best matches.

5 - To test the methods developed, using the databases, in order to access the overall performance of the algorithms and to optimize them by including expert knowledge.

6 - To integrate the identification methods into taxonomic and ecological database systems that include high-quality diatom images but also graphical representations of these consisting of the skeletons and characteristic points as derived from the model-based analysis methods.

As a result, this project aimed to generate software systems for slide scanning, autofocusing, image analysis, and pattern recognition, all optimized for diatom valve images. In parallel, large image databases were to be created, together with taxonomic and ecological descriptions.

Back to Top


The objectives mapped onto a number of tasks and subtasks. We present only a schematic organization of the tasks in order to give a coarse idea about how ADIAC functioned:
  • TASK 1: Image preprocessing and databases
  • Subtask 1a: Test image databases
    Subtask 1b: Image preprocessing and compression
    Subtask 1c: General image databases

    Image preprocessing served to normalize the contrast etc in order to facilitate feature extraction. Test image databases contained selected diatom images with increasing discrimination complexity. These served for testing the image analysis tools. General image databases contained samples of  relevant diatom species to be included in the taxonomic and ecological systems. These images were to be made available, together with analysis software, to all interested scientists.

  • TASK 2: Slide scanning, diatom localisation and autofocusing
  • Subtask 2a: Automatic slide scanning
    Subtask 2b: Autofocusing

    In this task the automation of slide scanning for diatoms was studied by linking a computer to a microscope and CCD camera. Because of the fact that diatom valves are three-dimensional (3D) objects, the exact criteria for autofocusing had to be studied in order to obtain the best images suited for a 2D analysis.

  • TASK 3: Diatom analysis and identification
  • Subtask 3a: Classical analysis
    Subtask 3b: Mathematical morphology
    Subtask 3c: Gabor wavelets
    Subtask 3d: Graph matching

    In task 3 several image processing tools were implemented and their performance evaluated in order to obtain the best algorithms. On the basis of a hierarchical graphical representation, matching was to be applied to link an unknown diatom to possible matches in the databases.

  • TASK 4: Identification tests
  • This task was the formal testing and evaluation work related to task 3, providing the feedback necessary for  algorithm optimization.

  • TASK 5: Integrated database systems
  • The original aim was to integrate the best image analysis algorithms, graph matching and the image databases to create a complete system for automated identification. Good progress was made, but full integration was not achieved.

  • TASK 6: Data management
  • Data management concerned not only the exchange of images etc between  partners, but also provision to other interested researchers, both from taxonomy and from pattern recognition. An ADIAC homepage with image databases and software was to be created (this is what you are reading right now!).

    Back to Top

    Collaborations beyond the partnership:

    The ADIAC project was a pilot study concerning the automation of diatom identification by means of computers. During the three years it was expected to realisz state-of-the-art algorithms and large image databases. However, it was the first project in which significant attempts were made to characterize diatom valve ornamentation. Hence, it was expected from the outset that the project would need a continuation (phase II) to further improve the analysis tools and to establish image databases that contain all diatom species relevant for certain applications/sites. The ultimate outcome of ADIAC might then be that one or two supercomputer centres would have the best analysis programs and all image databases, such that all interested researchers could send images in specific formats and get back a sorted list with the best matching species. In order to explore such a futuristic idea it was extremely important that ADIAC created also a database with potential users.

    Just as fingerprint processing became very "popular" after test images became publicly available, we hope that the same will occur for diatom processing. This field is still young and can provide challenging projects for students (graduating, MSc, PhD). Please refer also to the Public data pages.

    Back to Top

    Administrative details, partners, homepages, etc:

  • ADIAC started the 1st of May 1998
  • Duration 3 years
  • Total budget: 1250 kECU
  • Main funding: 850 kECU - European Commission
  • DG XII: MAST Programme (Marine Science and Technology)
  • Contract: MAS3-CT97-0122
  • Scientific Officer: Dr. K.-G. Barthel
  • Other funding: Swiss Government and CSIC Madrid
  • Partnership:

    Please note that some if not all partners will prepare their own ADIAC webpages as part of their institution/laboratory pages in order to show the people and activities. If you follow the links to the homepages, you will normally also find links to the institution's general webpages.

    Hans du Buf (coordinator)
    University of Algarve, Vision Laboratory
    Faculty of Exact Sciences and Humanities
    Campus de Gambelas - UCEH, 8000 Faro, Portugal
    Tel: +351 89 800900 ext 7761, fax: +351 89 818560
    Homepage: Vision Laboratory

    Horst Bunke
    Universitaet Bern
    Institut fuer Informatik und Angewandte Mathematik
    Neubrueckstr. 10, CH-3012 Bern, Switzerland
    Tel: +41 31 6314451, fax: +41 31 6313965
    Homepage: IAM at UBern

    Stephen Droop
    Royal Botanic Garden Edinburgh
    Diatom Laboratory
    20A Inverleith Row, Edinburgh EH3 5LR, UK
    Tel: +44 131 248 2975, fax: +44 131 248 2901 (changed!)
    Homepage: Algae World

    Jos Roerdink
    University of Groningen
    Inst. Mathematics and Computing Science
    Blauwborgje 3
    P.O.Box 800, 9700 AV Groningen, The Netherlands
    Tel: +31 50 3633931, fax: +31 50 3633800
    Homepage: Roerdink

    Stephen Juggins
    University of Newcastle upon Tyne
    Dept. of Geography
    Daysh Building, Claremont Road, Newcastle upon Tyne
    Tyne and Wear, NE1 7RU, UK
    Tel: +44 191 2228799, fax: +44 191 2225421
    Homepage: personal web-page

    Gabriel Cristobal
    Instituto de Optica (CSIC)
    Imaging and Vision Department
    Serrano 121, 28006 Madrid, Spain
    Tel: +34 1 5616800 ext 2319, fax: +34 1 5645557
    Homepage: Imaging and Vision Dept.

    Bertrand Ludes
    University Louis Pasteur
    Inst. for Legal Medicine - IML
    11, rue Humann, F-67085 Strasbourg Cedex, France
    Tel: +33 3 88249120, fax: +33 3 88356758 (changed!)

    Back to Top

    Public data

    One goal of ADIAC was to promote computer diatom processing, both in diatom research applications and in pattern recognition. To this end we have tried to make as much information available as possible: image databases, texts, literature lists, even software. You can use the information freely for research (non-profit) purposes if you acknowledge the project (ADIAC project; CEC contract MAS3-CT97-0122) in your reports and publications. Please don't forget to send us a copy! Software, when available, should include a header in the files with a reference to ADIAC.


    Back to Top

    Links and affiliations

    For ADIAC partner's homepage links, see Administrative details etc.

    Concerning the European Marine Science and Technology programme, you can go to the DG XII's MAST pages and the MAST-CORDIS server. Aditional information concerning the Environment and Climate programme can be found at the EUROPA and CORDIS servers.

    About diatom taxonomy, databases etc:

    For links to diatom websites, please go to the Algae World website, under 'links'

    About computer vision etc:

    An absolute must is to visit the Computer Vision Home Page, where you can find almost all (?) our vision colleagues in the world. For discussions, FAQs, etc, see the newsgroups sci.image.processing and Another useful source of information is Adrian Clark's PIXEL.

    Back to Top

    Address etc of the Coordinator: J.M.H. du Buf
    Homepage: dubuf

    Dept. of Electronics and Computer Science - UCEH,
    University of Algarve,
    Campus de Gambelas, 8000 Faro, Portugal

    Tel (+351 89) 800900 extension 7761 (is new number!)
    Fax (+351 89) 818560

    Back to the ADIAC FRONTPAGE

    Have a look at the University of Algarve, or go to the UAlg Vision Laboratory.

    Back to Top

    Don't forget Hein's Law:
    Problems worthy of attack prove their worth by hitting back

    Revised: August 2007 (David Mann)