In order to join the MICHE-II competition, each participant is asked to submit a registration form first. Once correctly registered, the participant can also submit one (and only one) executable application

Registration form (here)

1. Each participant to MICHE-II must fill and submit a registration form.
2. Each submission is associated to a username chosen by the participants. The username will be also used as a name for the submitted executable.
3. Each participant is allowed to submit only one executable.

Executable (here)

1. MICHE-II is a challenge for iris recognition on MICHEDB (a dataset of images grabbed by mobile devices and available online here). Each executable should therefore be able to receive from command line a pair of images from the dataset and a pair of corresponding segmentation masks and should produce a score in terms of dissimilarity between the two irises.
2. The order of inputs is strictly defined. Let
   
   • I₁ = image1Filename.ext be the first RGB image containing an iris;
   • M₁ = mask1Filename.ext be the binary mask of I₁;
   • I₂ = image2Filename.ext be the second RGB image containing an iris;
   • M₂ = mask2Filename.ext be the binary mask of I₂;
   • path be the directory for matching results;
   
   Let APP be the executable application, then by running:
   
   APP I₁ M₁ I₂ M₂ path
   a TXT file containing the dissimilarity_score is created. Such TXT file must have the following properties:
   
   1. it is saved in path (preferably something like "./results")
   2. its filename is image1Filename_image2Filename.txt (NOTE. filenames without file extensions)
   3. its content is image1Filename _[whitespace] image2Filename _[whitespace] dissimilarity_score (NOTE. filenames without file extensions)
3. The dissimilarity score is meant as the probability that two irises are from two different subjects. The higher is the dissimilarity the higher is the probability that the two irises are not from the same person. Let I be set of images from MICHEDB, the dissimilarity function D is defined as:
   
   where
   and satisfies the following properties:
   
   1. 
      
   2. 
      
   3. 
4. The participants can use the whole MICHEDB dataset for developing and performing experimentations of their proposed algorithm. The participants should take into account that the dataset is going to be extended with new acquisitions by new mobiles and of new subjects according to the same acquisition protocol applied to the current version of the database. The challenge will be run on a subset of the new version of MICHEDB that will be revealed together with the final ranking.
5. Participants must consider that the best segmentation algorithm submitted to MICHE-I will be used to generate the binary masks. Since it will be used also for the final ranking of submitted algorithms, participants are invited to use it for testing their proposal. Given an RGB image in input, the segmentation algorithm gives in output (a) the binary mask; (b) the normalised mask of the iris region; (c) the normalised RGB iris extracted from the image (see figures below):
   
   (a) (b) (c)
   Participants must consider that the only one segmentation result to be used by the proposed algorithm is the binary mask (a).
   The Unsupervised detection of non-iris occlusions (by Haindl et al.) is available for download here. For details of the algorithm, refer to the article published and available on-line in Elsevier Pattern Recognition Letters Journal.
   
6. Each executable is supposed to be self-contained and it will not have access to the Internet. No any additional download has to be expected to run the application. The submitted proposal must therefore contain all supporting files (dlls, libraries and so on) useful to its proper running.
7. The executable can be written in any programming language and should run on one of the following operating systems: (1) Windows 7 64/32 bit, (2) Linux Ubuntu 14.04. Code written in Matlab is also acceptable at condition that it runs on Matlab 2013. In case of any special setting needed for the proper running of the algorithm, a README file is expected.
8. Executables that do not match the requirements above could be discarded from the contest at the discretion of the Evaluating Committee.