With over decade of intensive research in the field of biometric, security based applications havebeen developed. There are many biometric security systemsfor person identificationbased on palm print, face, voice, iris, etc. Many researchers have recommended PCA as an efficient algorithm for such applications due to its simplicity, accuracy, and dimensionality reduction on large dataset while retaining as much as original information as possible. This paper presents the details of PCA tool for analyzing patterns in images. This paper focuses on choosing iris as a biometric for identification since it is unique of a person and it remains unchanged over many years (throughout the life of a person). CASIA v1 database has been used in the studies of PCA for personal identification. PCA gives 85% accuracy by using Euclidean distance as a classifier.

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Principal Component Analysis (pca) False Acceptance Rate(far) False Rejection Rate (frr) Chinese Academy Of Science Institute Of Automation (casia).