Fingerprint recognition or fingerprint authentication refers to the automated method of verifying a match between two human fingerprints. Fingerprints are one of many forms of biometrics used to identify individuals and verify their identity.
The main technologies used to capture the fingerprint image with sufficient detail are optical, silicon, and ultrasound. There are two main algorithm families to recognize fingerprints:
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Minutia matching compares specific details within the fingerprint ridges. At registration (also called enrollment), the minutia points are located, together with their relative positions to each other and their directions. At the matching stage, the fingerprint image is processed to extract its minutia points, which are then compared with the registered template.
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Pattern matching compares the overall characteristics of the fingerprints, not only individual points. Fingerprint characteristics can include sub-areas of certain interest including ridge thickness, curvature, or density. During enrollment, small sections of the fingerprint and their relative distances are extracted from the fingerprint. Areas of interest are the area around a minutia point, areas with low curvature radius, and areas with unusual combinations of ridges.
The two main functions of a biometrics system are storing and comparing. The storing process differs between different systems, as some systems store a great deal more information and will digitize and compress the information.
Once the print information is stored in an accessible database, a user's prints can be compared whenever the system is accessed. You are authenticated when both the stored and user's print match. Finger print readers use this uniqueness to generate a code
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rarely do they actually use the full print for identification
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based on areas where print lines merge, form, or loop like the round "whirl" that you can find in the middle
of all finger prints.
- Fingerprint recognition is one of the best known and most widely used biometric technologies. Automated systems have been commercially available since the early 1970s, and at the time of our study, we found there were more than 75 fingerprint recognition technology companies. Until recently, fingerprint recognition was used primarily in law enforcement applications. Fingerprint recognition technology extracts features from impressions made by the distinct ridges on the fingertips. The fingerprints can be either flat or rolled. A flat print captures only an impression of the central area between the fingertip and the first knuckle; a rolled print captures ridges on both sides of the finger.
Following were the commands being used:
Description: it reads a grayscale or color image from the file specified by the string filename. If the file is not in the current folder, or in a folder on the MATLAB path, specify the full pathname.
Description: it writes the image A to the file specified by filename in the format specified by format. Filename is a string that specifies the name of the output file.
Description: it displays a histogram for the image I above a grayscale color bar. The number of bins in the histogram is specified by the image type. If I is a grayscale image, imhist uses a default value of 256 bins. If I is a binary image, imhist uses two bins.imhist (I, n) displays a histogram where n specifies the number of bins used in the histogram. N also specifies the length of the color bar. If I is a binary image, n can only have the value 2.
Description: converts the true color image RGB to the grayscale intensity image I. Rgb2gray converts RGB images to grayscale by eliminating the hue and saturation information while retaining the luminance.
Description: It displays the grayscale image I, specifying the display range for Iin [low high]. The value low(and any value less than low) displays as black; the value high(and any value greater than high) displays as white. Values in between are displayed as intermediate shades of gray, using the default number of gray levels. If you use an empty matrix ([]) for [low high], imshow uses [min(I(:)) max(I(:))]; that is, the minimum value in Iis displayed as black, and the maximum value is displayed as white.