Last Update 29 January
Welcome to the Optimark homepage. Optimark is a benchmarking tool for still image watermarking algorithms that was developed in the Artificial Intelligence and Information Analysis Laboratory at the Department of Informatics, Aristotle University of
Thessaloniki, Greece. Its main features can be summarized as
- Graphical user interface.
- Detection/decoding performance evaluation using multiple trials utilizing different watermaking keys and
- Evaluation of the following detection performance metrics:
- For watermark detectors that provide a float output, i.e., the value of the test statistic used for detection:
- Receiver Operating Characteristic curves (ROC), i.e. plots of the probability of false alarm versus the probability of false rejection.
- Equal Error Rate.
- Probability of false alarm for a fixed, user defined, probability of false
- Probability of false rejection for a fixed, user defined, probability of false
- For watermark detectors that provide a binary output, i.e. a value that states whether the watermark has been detected or
- Probabilities of false alarm and false rejection.
- Evaluation of the following decoding performance metrics, for algorithms that allow for message encoding (multiple bit
- Bit error rate.
- Percentage (probability) of perfectly decoded messages.
- Evaluation of the mean embedding and detection time.
- Evaluation of the algorithm payload (for multiple bit algorithms).
- Evaluation of the algorithm breakdown limit for a certain attack and a certain performance criterion, i.e., evaluation of the attack severity where algorithm performance exceeds (or falls below) a certain
- Result summarization in multiple levels using a set of user defined weights on the selected attacks and
- Option for both user defined and preset benchmarking sessions.
The attacks that are currently included in Optimark are the following:
- No Attack
- Line and Column Removal
- General Linear Transformation
- Horizontal Flip
- Rotation + Autocropping
- Rotation + Autocropping + Autoscale
- Gaussian Filtering
The above attacks have been re-programmed from the Stirmark benchmark.
If you use the Optimark tool for your research, please cite the following paper:
V. Solachidis, A. Tefas, N. Nikolaidis, S. Tsekeridou, A. Nikolaidis, I.Pitas,
``A benchmarking protocol for watermarking methods’’, 2001 IEEE Int. Conf. on Image Processing (ICIP'01), pp. 1023-1026, Thessaloniki, Greece, 7-10 October, 2001
Reading this paper before using Optimark is highly recommended.
Please send your comments and bug reports to firstname.lastname@example.org
Optimark was partially supported by EU Projects CERTIMARK &