Iris Database Compression Using Haar Wavelet Decomposition and Huffman Coding

Abstract: Iris recognition system for identity authentication and verification is one of the most precise and accepted biometrics in the world. The need for portable iris system has been increasing more rapidly which demands efficient compression techniques for its transmission through a narrow-bandwidth communication channel. In spite of rapid progress in mass storage density and processor speeds, this demand continues. This paper has investigated the effects of iris image compression based on Haar Wavelet Decomposition and subsequent Huffman Coding. The results have been examined in terms of Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Compression Ratio (CR). It has been found that Huffman Coding transform is an effective lossless image compression technique, as recognition performance is minimally affected and the use of Haar transform is well suited. The matching stage is implemented using Euclidean distance calculation and CASIA iris database has been used for the study.

Keywords: Iris recognition; Image compression and decomposition; Haar wavelet transform; Huffman coding; Peak signal to noise ratio