Now-a-day fingerprint matching is considered as a subset of biometrics. It plays an important role in offices and industries to register the attendance of the employees, and in forensic departments for criminal identification. Although minutia based detection has gained more popularity, but it shows poor performance in case of low quality images. Whereas correlation based methods provides better results for such images. In this paper we propose a new correlation method based on the sum of hamming distance between the reference fingerprint in database and intruding fingerprint. The proposed method involves bit level computing operations and less preprocessing steps, thus faster than other conventional correlation based matching. We have also compared the results with the existing methods available in the literature to show its effectiveness.