Contact Lens Classification by Using Segmented Lens Boundary Features

Nur Ariffin Mohd Zin (Universiti Tun Hussein Onn Malaysia)
Hishammuddin Asmuni (Universiti Teknologi Malaysia)
Haza Nuzly Abdul Hamed (Universiti Teknologi Malaysia)
Razib M. Othman (Universiti Teknologi Malaysia)
Shahreen Kasim (Universiti Tun Hussein Onn Malaysia)
Rohayanti Hassan (Universiti Teknologi Malaysia)
Zalmiyah Zakaria (Universiti Teknologi Malaysia)
Rosfuzah Roslan (Universiti Tun Hussein Onn Malaysia)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 11, No 3: September 2018

Recent studies have shown that the wearing of soft lens may lead to performance degradation with the increase of false reject rate. However, detecting the presence of soft lens is a non-trivial task as its texture that almost indiscernible. In this work, we proposed a classification method to identify the existence of soft lens in iris image. Our proposed method starts with segmenting the lens boundary on top of the sclera region. Then, the segmented boundary is used as features and extracted by local descriptors. These features are then trained and classified using Support Vector Machines. This method was tested on Notre Dame Cosmetic Contact Lens 2013 database. Experiment showed that the proposed method performed better than state of the art methods.