Transactions on Machine Intelligence 2821-1693 4 3 2021 09 01 Identity Recognition from Ear Images Using Local Binary Pattern and Local Phase Quantization 128 136 218653 10.47176/TMI.2021.128 EN A. Fathi Assistant Professor, Department of Computer Science and Information Technology, Razi University, Kermanshah, Iran Sh. Sajjadi M.Sc. Student in Information Technology Engineering, Department of Computer Science and Information Technology, Razi University, Kermanshah, Iran Journal Article 2021 05 03 One of the challenges posed by technological advancements in modern society is the issue of identity verification and authentication. Among various biometric identification methods, ear biometrics is a relatively new approach. Identity recognition has garnered significant attention in the realm of biometrics, particularly with the advancement of image processing techniques. Among various biometric traits, ear recognition is emerging as a reliable method due to the unique structure of human ears. The human ear possesses unique characteristics that make it suitable for identity recognition. In this study, we employ Local Binary Pattern (LBP) and Local Phase Quantization (LPQ) operators for pattern recognition in ear images. To reduce the feature vector size and enhance classifier accuracy, we apply Principal Component Analysis (PCA) to the features extracted using LBP. Finally, we utilize the k-Nearest Neighbors (k-NN) algorithm with the Canberra similarity measure for classification. To evaluate the efficiency of our proposed method, we conducted experiments on the USTB-1 database, which contains 180 images from 60 individuals, achieving an accuracy of 98.33%. https://www.tmachineintelligence.ir/article_218653_a3dd6041c26f6ccabad08f6dc5fbd622.pdf