Introduction
This report is about the biometric and the methods used in it. Matching modes of fingerprints and its benefits are also discussed below.
Advantage and disadvantage of fingerprint recognition
Advantages:
- · Fake fingerprints are difficult to use so this method is considered as a high-level security system.
- The validation technique is well developed and easy to use.
- Less space is taken from the large database because the templates in biometric use small storage area.
- It gives exact and positive identification.
- It is a cheap technology which offers mobility.
- It’s safe and its key cannot be transferred to anyone.
Disadvantages:
- This system does not provide any modification in cases like illness, injury or aging.
- Environmental conditions affect the process of sample collection like lighting, facial recognition or expressions.
- It is intrusive for some people because criminal cases are linked to it.
- The identity information can be stolen from the devices which can cause damage.
- It is not possible for the scanners to identify whether it is a real or an artificial fingerprint.
Correlation-based matching
The method in which the one image covers the other image is called Correlation based matching. Moving any one of the images results in the change of the image alignment and it continues till the pixels of both the images are maximized. The correlation of every corresponding pixel is determined through computing and aligning the fingerprints. As displacement and rotation are unknown so it is possible and required to determine the correlation of all alignments.
This method does not support much for contrast variation and non-linear distortion also the computation is complex because of the reason that more time is needed and more resources are required for pixel by pixel matching of images. There are few methods in which all pixels are not matched but only one pixel is matched.
correlation-based matching
Minutiae Based Matching
Minutiae are one of the distinguished points of the fingerprint which is rarely known. At minutiae points the Ridgelines from their path break down. In this method, the stored templates are aligned with these points of the input image. Correct alignments can be calculated by using various available methods. Commercial applications especially for the quality images this method is used as it takes very less computational time. It is most commonly used in automatic fingerprint recognition systems. This method is used for the comparison of fingerprints by forensic experts. It is difficult to extract minutiae if the quality of fingerprint image is bad. So to overcome this situation ridge-feature-based matching is used.
Minutiae Based Matching
Ridge feature-based matching
The basics in ridge feature-based matching are ridge frequency, ridge orientation, texture, amount of ridges between the minutiae and shape. This method is used where the finger code is the difference between the two vectors of the finger code. The finger code is implemented after the alignment of the fingerprint images. This is considered as a drawback if compare to various other methods. Singularity is another matching method and in the minutiae-based method, it is complementary to use finger code. Original methods include circular finger code where the center is the core point.
Ridge feature-based matching
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