Improved PCA-Based Personal Identification Method Using Invariance Moment

Abstract

Since PCA-based teeth-image personal identification method (K. Prajuabklang, et al., 2004) is not robust against reflection and orientation, registered persons in database are rejected around 7%. This paper proposes a method to improve the PCA-based teeth-image personal identification method. In this method, the teeth image failed from the matching in the PCA-based system is reconsidered by feeding back the image to eliminate the reflection and the rotation problems. The enhanced teeth image is fed back to PCA process in order to rescue misclassified teeth-image. In the experiments, 25 teeth images are tested with 20-teeth database. The results revealed that of the 7% errors caused by the two problems, 5% are correctly identified because of the proposed method