Synthetic Iris Model Based

The gallery of synthetic iris images are generated in five steps using a model based, anatomy based approach, with 40 controllable random parameters such as fiber size, pupil size, iris thickness, top layer thickness, fiber cluster degree, iris root blur range, the location of the collaret, the amplitude of the collaret, top layer transparency parameter, eye angle, eye size etc. The software coded with Matlab, generates 10000 classes (5000 subjects, left and right eye). Each class has 16 images, 1 good quality image, 15 degenerated images, with combination effects among noise, rotation, blur, motion blur, low contrast and specular reflection. For each image segmentation results ( unwrapped template, enhanced template and occlusion mask) are provided.

Performance is evaluated using a traditional Gabor filter based system. A comprehensive comparison of synthetic and real data is performed at three levels of processing: (1) image level, (2) texture level , and (3) decision level. A sensitivity analysis is performed to conclude on importance of various parameters involved in generating iris images.

1.  Generate continuous fibers in 3D cylindrical coordinates.

Synthetic Iris Model Based

2.  Project 3D fibers into a 2D flat image space.

Synthetic Iris Model Based

3.  Transform the basis image to include the effect of collaret. Add a semitransparent top layer with an irregular edge.

Synthetic Iris Model Based

4.  Blur the iris root and add a random bumpy pattern to the top layer.

Synthetic Iris Model Based

5.  Add the eyelids at a certain degree of opening and randomly generated eyelashes.

Synthetic Iris Model Based

Examples of synthetic iris images:

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When using synthetic iris images please cite:
Zuo J., Natalia A. Schmid,_ On Generation and Analysis of Synthetic Iris Images,_ IEEE Transactions on Information Forensics and Security, volume 2, issue 1, March 2007, pages 77 to 90.

CITeR: Center for Identification Technology Research

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