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Biometric techniques have inherent advantages over traditional personal identification technique. Biometric techniques uses a mechanism to scan and capture a digital or analog image of a living personal characteristic and a matching system to match input biometric image to stored biometric templates. Among various commercially available biometric techniques such as face, fingerprint, Iris etc., fingerprint-based techniques are the most popular recognition system. Fingerprints are imprints or impressions of patterns formed by friction ridges of the skin in the fingers and thumbs. Steganography generally used in smart card is a secure technique for authenticating a person. In steganography biometric characteristic like fingerprint is hidden in an image. At the time of recognition, the individual's characteristics are being measured against hidden characteristic that is stored. Since the amount of information that can be stored by means of steganography is very limited, compression mechanisms are required in order to achieve reasonably small errors when finally checking fingerprints against the encoded templates. To reduce the size of smart card, compression can be applied to fingerprint template in order to make it take up less space. This paper is presenting the minutiae based low cost fingerprint compression technique. In minutiae-based systems, the discontinuities in the regular ridge structure of fingerprint images, called ridge ending, ridge bifurcation, core, cross-over, delta, pore etc., are identified in feature extraction stage. During matching, a similarity value between the features extracted from the template and the input fingerprint images is calculated. This similarity value is used to arrive at an accept/reject decision. We present a new approach based on delta compression for strongly compressing the fingerprint templates.