Fingerprint verification systems that are already made available to the world are developed on their respective platforms. Among them, each system has its particular way of verification and matching. Fingerprint identification is becoming increasingly automated. Automated fingerprint identification system (AFIS) has provided the most popular and successful solution, mainly due to the uniqueness of fingerprints and the historical legal aspect of fingerprinting for law enforcement. As advantages of automatic fingerprint identification systems become more apparent through widespread use, automated fingerprint identification systems are becoming more common and more widely used. An automatic fingerprint identification operation normally consists of two stages. The first is the registration or enrollment stage and the second is the identification, authentication or verification stage. Automated fingerprint identification systems input an electronic representation of an unknown fingerprint for use in selection of one or more matching prints from a massive body of stored electronic representations of many fingerprints. Two types of matching applications are used for fingerprints. One-to-one verification is used to compare a fingerprint with either a particular template or a template recovered from a database by having the person provide his or her name, or personal identification number (PIN) code. One-to-many identification is used to compare a fingerprint to a database of templates, and is required when a person presents only his or her finger which is then compared to a number of stored images. Automated fingerprint identification system includes features such as fingerprint image pre-enhancement, orientation filtering, ridge thinning, fingerprint registration and weighted matching score computation. A fingerprint verification device is used to compare a fingerprint image, which has been collected from a person to be identified, with a registered fingerprint image in order to determine whether the person to be identified is in the register. A fingerprint capture and verification systems include mechanisms for optically capturing images of a fingerprint, mechanisms for optically comparing or interrogating records of fingerprint images with contemporaneous fingerprint images, and signal comparison/computational processors for analyzing and providing output indicative or as a consequence of a match between a permanent fingerprint record and a contemporaneously captured fingerprint image. There are several techniques to acquire a fingerprint including scanning an inked fingerprint and inkless methods using optical, capacitative or other semiconductor-based sensing mechanisms. The acquired biometric signal is processed and matched against a stored template. The image processing techniques typically locate ridges and valleys in the fingerprint and derive the templates from the ridge and valley pattern of a fingerprint image.

Fingerprint image input devices used to input fingerprint images include: image sensor, line scanner, planar scanner, contact image sensor, charge-coupled device (CCD) sensor, CMOS sensor, chip sensor etc. Among them, image sensor, line scanner, planar scanner, CMOS sensor and contact image sensor are optical image input devices, in which the contact image sensor is a sensor where light source and image sensor are combined as one element. The chip sensor is an electronic sensor which, according to the distribution of capacitances and electric fields, obtains the topographic image data of a fingerprint. Fingerprint scanners or fingerprint readers have become one of the more common, commercially available biometric security devices. They operate on the principle that every person has fingerprint pattern that is unique to each person. A typical optical fingerprint scanner consists of a charge-coupled device (CCD) camera and an internal light source. The internal light will illuminate the fingerprint and the carmera will capture the reflected image. A typical frame capture rate is on the order of about several dozen times per second. By comparing successive live images or groups of successive images, the scanner can determine if the image is changing. As computer and scanner technologies have advanced, the benefits of fingerprint identification have been exploited in increasing number applications by an increasing number of users. High performance computers permit an initial automated matching of a sample set, or search set, of fingerprints against a massive fingerprint database. Fingerprint scanners having cameras are available that capture an image of a fingerprint. A signal representative of the captured image is then sent over a data communication interface to a host computer for further processing. A typical electronic fingerprint sensor is based upon illuminating the finger surface using visible light, infrared light, or ultrasonic radiation. The reflected energy is captured with some form of camera, and the resulting image is framed, digitized and stored as a static digital image. A rolled fingerprint scanner is a device used to capture rolled fingerprint images. The scanner captures the image of a user's fingerprint as the user rolls a finger across an image capturing surface. Multiple fingerprint images may be captured by the scanner as the finger is rolled.