International Journal of Scientific & Technology Research Volume 1, Issue 3, April 2012 ISSN 2277-8616 31 IJSTR'2012 www.ijstr.org A Novel Pre-processing Technique for DCT- domain Palm-print Recognition Hafiz Imtiaz, Shubhra Aich, Shaikh Anowarul Fattah Abstract In this paper, a novel pre-processing algorithm is introduced to identify the principal lines from a palm-print image and a discrete cosine transform (DCT) domain feature extraction algorithm is then employed for palm-print recognition, which can efficiently capture the spatial variations in the principal lines of a palm-print image. The entire image is segmented into several small spatial modules. The task of feature extraction is carried out in local zones using two dimensional discrete cosine transform (2D-DCT). The proposed dominant DCT-domain feature selection algorithm offers an advantage of very low feature dimension and it is capable of capturing precisely the detail variations within the palm- print image. It is shown that because of the pre-processing step, the discriminating capabilities of the proposed features are enhanced, which results in a very high within-class compactness and between-class separability of the extracted features. From our extensive experimentations on different palm-print databases, it is found that the performance of the proposed method in terms of recognition accuracy and computational complexity is superior to that of some of the recent methods. Index Terms Spectral feature extraction, binary palm image, two-dimensional discrete cosine transform, classification, palm- print recognition, entropy, modularization. ------------------------------------------------------------------------ 1.INTRODUCTION CONVENTIONAL ID card and password based identification methods, although very popular, are no more reliable as before because of the use of several advanced techniques of forgery and password-hacking. As an alternative, biometrics, such as palm-print, finger-print, face and iris being used for authentication and criminal identification [1]. The main advantage of biometrics is that these are not prone to theft and loss, and do not rely on the memory of their users. Moreover, they do not change significantly over time and it is difficult for a person to alter own physiological biometric or imitate that of other persons. Among different biometrics, in security applications with a scope of collecting digital identity, the palm-prints are recently getting more attention among researchers [2]. Palm-print recognition methods are based on extracting unique major and minor line structures that remain stable throughout the lifetime. In this regard, generally, either line- based or texture-based feature extraction algorithms are employed [3]. In the line- based schemes, generally, different edge detection methods are used to extract palm lines (principal lines, wrinkles, ridges, etc.) [4], [5]. The extracted edges, either directly or being represented in other formats, are used for template matching. In cases where more than one person possess similar principal lines, line based algorithms may result in ambiguous identification. In order to overcome this limitation, the texture-based feature extraction schemes can be used, where the variations existing in either the differ- ent blocks of images or the features extracted from those blocks are computed [6]-[8]. Given the extracted features, various classifiers, such as decision-based neural networks and Euclidean distance based classifier, are employed for palm- print recognition [4], [5]. Despite many relatively successful attempts to implement face or palm-print recognition system, a single approach, which combines accuracy, robustness, and low computational burden, is yet to be developed. The objective of this paper is to identify the principal lines from a palm-print image and extract precisely spatial variations from each local zone of the entire palm-print image instead of concentrating on a single global variation pattern. In the proposed palm-print recognition scheme, the entire palm-print image of a person is segmented into several small modules. An efficient feature extraction scheme using 2D-DCT, which offers an ease of implementation in practical applications, is developed, which operates within those local zones to extract dominant spectral features. In comparison to the discrete Fourier transform, the DCT is used as it can efficiently handle the phase unwrapping problem and offer energy compactness as well as computational advantages. It is shown that the discriminating capabilities of the proposed features, that are extracted from the sub-images, are enhanced because of the pre-processing step and also for the modularization of the palm-print image. Finally, recognition task is carried out using a distance based classifier. 2 PRE-PROCESSING A key issue to be solved for successful palm-print recognition is preprocessing of the palm-print image to gain a proper sub-   Hafiz Imtiaz is currently an Assistant Professor with the Department of Electrical and Electronic Engineering in Bangladesh University of Engineering and Technology, Dhaka- 1000, Bangladesh. E-mail: hafizimtiaz@eee.buet.ac.bd  Shubhra Aich is currently an undergraduate student with the Department of Electrical and Electronic Engineering in Bangladesh University of Engineering and Technology, Dhaka- 1000, Bangladesh.  Shaikh A. Fattah is currently an Associate Professor with the Department of Electrical and Electronic Engineering in Bangladesh University of Engineering and Technology, Dhaka- 1000, Bangladesh. E-mail: fattah@eee.buet.ac.bd