The First CCBR Competition on Iris Recognition （CCIR2014）
With the pronounced need for reliable personal identification, iris recognition has become an important enabling technology in our society. Although an iris pattern is naturally an ideal identifier, the development of a high-performance iris recognition algorithm and transferring it from research lab to practical applications are still a challenging task. Automatic iris recognition has to face unpredictable variations of iris images in real-world applications. Therefore the first CCBR Competition on Iris Recognition (or CCIR2014 shortly) is organized to track the state-of-the-art of iris recognition.
CCIR2014 is open to both academia and industry. There are two iris image databases used in CCIR2014 for training and testing purposes, respectively. The training database(CASIA-Iris-Lamp) contains 16,212 iris images of 411 subjects. CASIA-Iris-Lamp was collected using a hand-held iris sensor produced by OKI. All iris images of CASIA-Iris-Lamp are 8 bit gray-level BMP files and the image resolution is 640×480 (Fig. 1). The testing database (or IR-TestV1)contains 5,000 iris images of 1,000 eyes. The iris images of IR-TestV1 were captured using OKI camera in one session. Each volunteer contributed 10 iris images of both left and right eyes, i.e. 5 images each class. The main sources of intra-class variations in IR-TestV1 are non-linear deformations, eyeglasses and specular reflections. All iris images of IR-TestV1 are 8-bit gray-level BMP files and the image resolution is 640×480 (Fig. 2).
Fig. 1 Example iris images in the training database
Fig. 2 Example iris images in the testing database
All participants should submit two executables "irisenroll_AlgorithmName.exe" and "irismatch_AlgorithmName.exe" in the form of Win64 console applications for third-party performance evaluation. Moreover, a document including a brief introduction and a flowchart about the submitted algorithm is needed. The file "irisenroll_AlgorithmName.exe" is used to generate a feature template from an iris image. The file "irismatch_AlgorithmName.exe" is used to match two iris feature templates. The syntax of the two executables through command-line is as follows.
>irisenroll_AuthorName imagefile templatefile outputfile
> irismatch_AuthorName templatefile1 templatefile2 outputfile
All possible intra-class comparisons are implemented to evaluate the false non-match rate (FNMR) providing a total of 10,000 intra-class match results. One sample is selected from each iris class to evaluate the false match rate (FMR) so there are totally 499,500 inter-class match results. If an intra- or inter-class comparison cannot be successfully implemented due to failure enrollment or failure match, a random variable ranging from 0 to 1 will be assigned as the matching score. Popular performance metrics of iris recognition such as FNMR, FMR, EER and ROC will be reported and the metric F4(FNMR@ FMR=0.0001) will be used to rank the performance of submitted algorithms.
Each participant can maximally submit three algorithms. We only accept qualified iris recognition algorithms which meet the following requirements due to limited competition resources:
• The equal error rate (EER) must be less than 5% on the training database.
• The average processing time for feature encoding must be less than 3 seconds and the average matching time must be less than 0.1 second on a normal personal computer.
A public platform, the Biometrics Ideal Test (BIT; http://biometrics.idealtest.org) is used to organize the competition. The competition registration process is as follows.
1. Register an account in BIT (http://biometrics.idealtest.org ) and select the option "Participant of CCBR Competition on Iris Recognition".
2. Download the training database CASIA-Iris-Lamp after your account is approved and activated.
3. Develop an iris recognition algorithm and you can use the CASIA-Iris-Thousand or other iris image databases as the training data.
4. Submit your algorithm to email@example.com. If size of the algorithm file is too large, you can also send us a web link for download. To help users quickly master the programming protocols of algorithm evaluation, the source codes of the example files "enroll.c" and "match.c" are provided for download as below. Download C language source code here
5. Any problem of your algorithm during testing will be reported to you so please respond immediately to the organizers of CCIR2014.
6. The CCIR2014 Competition Committee will report the performance of all submitted algorithms and the competition results.
7. Authors of the winner algorithm will be invited to write a paper on their algorithm to be published in the CCBR2014 proceedings.
Any questions on CCIR2014 can be addressed by emailing firstname.lastname@example.org.
Open of the competition April 1, 2014
Deadline of algorithm submission June 30, 2014
Release of the testing results During the CCBR2014