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Fingerprint Recognition System Abstract Fingerprint recognition system consist of image preprocessing, features extraction and features matching that runs effectively and accurately on personal computer. The image preprocessing includes noise removal, histogram equalization, global thresholding and ridgeline thinning which are necessary for the features extraction. Extracted features are then stored in a file for fingerprint matching. Matching algorithm presented here is a simple, fast and accurate. Experimental results for matching are accurate, reliable and fast for implementation using a personal computer and fingerprint reader. The proposed fingerprint algorithm can provide an effective way of automated identification and can be extended to other security or identification applications. Further the algorithm can be implanted on a FPGA platform for a real time personal automated identification system. Keywords:biometric recognition;histogram equalization;ridge thinning;ridge ending;ridge bifurcation. 1. INTRODUCTION Fingerprint recognition systems are termed under the umbrella of biometrics. Biometric recognition refers to the distinctive physiological (e.g. fingerprint, face, iris, retina) and behavioral (e.g. signature, gait) characteristics, called biometric identifiers or simply biometrics, for automatically recognizing individuals. In 1893, it was discovered that no two individuals have same fingerprints. After this discovery fingerprints were used in criminal identification and till now fingerprints are extensively used in various identification applications in various fields of life. Fingerprints are graphical flow-like ridges present on human fingers. They are fully formed at about seventh month of fetus development and fingerprint configuration do not change throughout the life except due to accidents such as bruises or cut on fingertips. Because of immutability and uniqueness, the use of fingerprints for identification has always been of great interest