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Palmprint based personal verification is an accepted biometric modality due to its reliability, ease of acquisition and user acceptance. This paper presents a novel palmprint based identification approach which draw on the textural information available on the palmprint by utilizing a combination of contourlet and non subsampled contourlet transforms. Center of the palm is computed using the distance transform whereas the parameters of best fitting ellipse help determine the alignment of the palmprint. ROI of 256×256 pixels is cropped around the center, and subsequently it is divided into fine slices, using iterated directional filterbanks. Next, directional energy components for each block of the decomposed subband outputs are computed using contourlet and non subsampled contourlet transforms. The proposed algorithm captures global details in a palmprint as compact fixed length palm codes for contourlet and …