Palmprint Image Identification Using PCA, LBP and HOG Features

Biometrics considered as the science which is playing an important role of person recognition. User identification mainly based on the physiological characteristics of an individual. Palmprint is an example of physiological characteristics of an individual which can be easily captured by using some types of sensors and cameras. The palmprint has many nature compositions which contain rich features that mainly used for distinguishing such as, wrinkles, ridges, principal lines, singular and minutiae points, these make a palmprint as one of a unique biometric and reliable for human recognition. In this work different features extraction algorithms were used such as a texture based method (LBP, HOG), and appearance based method (PCA). Also K-Cross Validation algorithm was implemented. The accuracy rates of recognition results of implemented algorithms were acquired and compared. Keywords: Biometric, Palmprint, Accuracy rates and Recognition algorithms.