Implementing Centre-Symmetric Local Binary Pattern (CS-LBP) In Raspberry PI For Iris Recognition - Abdullah, Muhammad Firdaus (Universiti Sains Malaysia, 2018)
The human iris, like fingerprints, has an amazing characteristic where it is unique to every person. Like fingerprints, iris is often use in biometric system for identification and security. Currently, there are many methods for image identification, enhancement, compression and many other image processing applications. The focus of this project is to apply a known descriptor called the Centre-Symmetric Local Binary Pattern (CS-LBP),for iris recognition. The CS-LBP method will be applied to an image of a human iris that had undergo segmentation and detection process for feature extraction. These features will describe all individual iris where it will then be tested using a classifier in order to determine the reliability of the applied method to classify different iris pattern with different people. The CS-LBP is shown to have a few advantages given its computational-friendly operations. It describes the texture and grey-levels of an image by comparing the centre-symmetric pairs of opposite pixels in reference to the centre pixel. The descriptor also has tolerance to illumination changes, robustness on flat image areas and computational efficiency. All this process will be implemented in a small, low-cost computer called the Raspberry Pi 3B. The purpose of implementing this iris recognition program into the Raspberry Pi is that the Raspberry Pi is a cheap yet powerful platform. The small size of the computer also helps with portability of the device if it can be further integrated into a hand carry-on device. This can be further applied into the security sector for executing an iris recognition program. A Graphical User Interface (GUI) will also be developed for an easy interaction between user and the program.