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ImageCLEF 2019 Coral - Annotation and Localisation



Note: ImageCLEF Coral 2019 is divided into 2 subtasks (challenges). This challenge is about Annotation and Localisation. For information on the Pixel-wise Parsing challenge click here . Both challenges share the same dataset, so registering for one of these challenges will automatically give you access to the other one.

Note: Do not forget to read the Rules section on this page.


The increasing use of structure-from-motion photogrammetry for modelling large-scale environments from action cameras attached to drones has driven the next-generation of visualisation techniques that can be used in augmented and virtual reality headsets. It has also created a need to have such models labelled, with objects such as people, buildings, vehicles, terrain, etc. all essential for machine learning techniques to automatically identify as areas of interest and to label them appropriately. However, the complexity of the images makes impossible for human annotators to assess the contents of images on a large scale. Advances in automatically annotating images for complexity and benthic composition have been promising, and we are interested in automatically identify areas of interest and to label them appropriately for monitoring coral reefs. .Coral reefs are in danger of being lost within the next 30 years, and with them the ecosystems they support. This catastrophe will not only see the extinction of many marine species, but also create a humanitarian crisis on a global scale for the billions of humans who rely on reef services. By monitoring the changes and composition of coral reefs we can help prioritise conservation efforts.

Challenge description

This task requires the participants to label the images with types of benthic substrate together with their bounding box in the image. Each image is provided with possible class types. For each image, participants will produce a set of bounding boxes, predicting the benthic substrate for each bounding box in the image.


The data for this task originates from a growing, large-scale collection of images taken from coral reefs around the world as part of a coral reef monitoring project with the Marine Technology Research Unit at the University of Essex. Substrates of the same type can have very different morphologies, color variation and patterns. Some of the images contain a white line (scientific measurement tape) that may occlude part of the entity. The quality of the images is variable, some are blurry, and some have poor color balance. This is representative of the Marine Technology Research Unit dataset and all images are useful for data analysis. The images contain annotations of the following 13 types of substrates: Hard Coral – Branching, Hard Coral – Submassive, Hard Coral – Boulder, Hard Coral – Encrusting, Hard Coral – Table, Hard Coral – Foliose, Hard Coral – Mushroom, Soft Coral, Soft Coral – Gorgonian, Sponge, Sponge – Barrel, Fire Coral – Millepora and Algae - Macro or Leaves.

The training set contains contains 240 images with 6670 substrates annotated. Two files are provided with ground truth annotations: one based on bounding boxes “imageCLEFcoral2019_annotations_training_task_1” and a more detailed annotation based on bounding polygon “imageCLEFcoral2019_annotations_training_task_2”. The test set contains 200 images.

The data can be downloaded from the “Dataset” tab and will be made available on:

  • 04.02.2019 Training data

  • 18.03.2019 Test data

Submission instructions

As soon as the submission is open, you will find a “Create Submission” button on this page (just next to the tabs)

The submissions will be received through the crowdai system.

Participants will be permitted to submit up to 10 runs. External training data is allowed and encouraged.

Each system run will consist of a single ASCII plain text file. The results of each test set should be given in separate lines in the text file. The format of the text file is as follows:

[image_ID/document_ID] [results]

The results of each test set image should be given in separate lines, each line providing only up to 500 localised substrates. The format has characters to separate the elements, semicolon ‘;’ for the substrates, colon ‘:’ for the confidence, comma ‘,’ to separate multiple bounding boxes, and ‘x’ and ‘+’ for the size-offset bounding box format, i.e.:

[image_ID];[substrate1] [[confidence1,1]:][width1,1]x[height1,1]+[xmin1,1]+[ymin1,1],[[confidence1,2]:][width1,2]x[height1,2]+[xmin1,2]+[ymin1,2],…;[substrate2] ..

[confidence] are floating point values 0-1 for which a higher value means a higher score.

For example, in the development set format (notice that there are 2 bounding boxes for substrate c_soft_coral):

  • 2018_0714_112604_057 0 c_hard_coral_branching 1 891 540 1757 1143
  • 2018_0714_112604_057 3 c_soft_coral 1 2724 1368 2825 1507
  • 2018_0714_112604_057 4 c_soft_coral 1 2622 1576 2777 1731

In the submission format, it would be a line as:

  • 2018_0714_112604_057;c_hard_coral_branching 0.6:867x 604+891+540;c_soft_coral 0.7:102x140+2724+2825,0.3:156x156+2622+1576


Information will be posted after the challenge ends.



More on the evaluation criteria will be published soon.


Note: In order to participate in this challenge you have to sign an End User Agreement (EUA). You will find more information on the ‘Dataset’ tab.

ImageCLEF lab is part of the Conference and Labs of the Evaluation Forum: CLEF 2019. CLEF 2019 consists of independent peer-reviewed workshops on a broad range of challenges in the fields of multilingual and multimodal information access evaluation, and a set of benchmarking activities carried in various labs designed to test different aspects of mono and cross-language Information retrieval systems. More details about the conference can be found here .

Submitting a working note with the full description of the methods used in each run is mandatory. Any run that could not be reproduced thanks to its description in the working notes might be removed from the official publication of the results. Working notes are published within CEUR-WS proceedings, resulting in an assignment of an individual DOI (URN) and an indexing by many bibliography systems including DBLP. According to the CEUR-WS policies, a light review of the working notes will be conducted by ImageCLEF organizing committee to ensure quality. As an illustration, ImageCLEF 2018 working notes (task overviews and participant working notes) can be found within CLEF 2019 CEUR-WS proceedings.


Participants of this challenge will automatically be registered at CLEF 2019. In order to be compliant with the CLEF registration requirements, please edit your profile by providing the following additional information:

  • First name

  • Last name

  • Affiliation

  • Address

  • City

  • Country

  • Regarding the username, please choose a name that represents your team.

This information will not be publicly visible and will be exclusively used to contact you and to send the registration data to CLEF, which is the main organizer of all CLEF labs

Participating as an individual (non affiliated) researcher

We welcome individual researchers, i.e. not affiliated to any institution, to participate. We kindly ask you to provide us with a motivation letter containing the following information:

  • the presentation of your most relevant research activities related to the task/tasks

  • your motivation for participating in the task/tasks and how you want to exploit the results

  • a list of the most relevant 5 publications (if applicable)

  • the link to your personal webpage

The motivation letter should be directly concatenated to the End User Agreement document or sent as a PDF file to bionescu at imag dot pub dot ro. The request will be analyzed by the ImageCLEF organizing committee. We reserve the right to refuse any applicants whose experience in the field is too narrow, and would therefore most likely prevent them from being able to finish the task/tasks.


ImageCLEF 2019 is an evaluation campaign that is being organized as part of the CLEF initiative labs. The campaign offers several research tasks that welcome participation from teams around the world. The results of the campaign appear in the working notes proceedings, published by CEUR Workshop Proceedings (CEUR-WS.org). Selected contributions among the participants, will be invited for publication in the following year in the Springer Lecture Notes in Computer Science (LNCS) together with the annual lab overviews.


Contact us

We strongly encourage you to use the public channels mentioned above for communications between the participants and the organizers. In extreme cases, if there are any queries or comments that you would like to make using a private communication channel, then you can send us an email at :

  • Jon Chamberlain <jchamp(at)essex.ac.uk>,University of Essex, UK

  • Adrian Clark <alien(at)essex.ac.uk>,University of Essex, UK

  • Antonio Campello <antonio.campello(at)filament.ai>,Filament, UK

  • Alba García Seco de Herrera <alba.garcia(at)essex.ac.uk>,University of Essex, UK

More information

You can find additional information on the challenge here: https://www.imageclef.org/2019/coral