Fingerprint recognition algorithm using phase-based image matching

Published on 14 Jun 2021. Written by Amitesh Kumar

Overview

The fingerprint recognition system is not new for any of us; we have seen it many times. The system which scans the image of the finger is largely dependent on the surface of the fingers. Fingertips skin can get smoothen through time or moist which can produce hindrance in recognizing the pattern. Addressing 2D picture of the fingerprint is quite difficult so we will need some procedure to adhere to this problem. 

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SLNOTE
Procedure

In this MATLAB project, we will make a project to identify the fingerprints well. With the help of MATLAB, we can build such a project that can manipulate these scanned images. In the following project we will be using a sensor, then a Minutia Extractor and then finally Minutiae Matcher. All the process includes scanning, manipulating and then matching with the save data.

A lot of mathematical functions are required to fulfil the project needs. The mathematical functions used such as False Accept Rate, False Reject rate, and the difference between the intensity of the pixel in the project. For the correct manipulation of these mathematical operations, we will need the help of MATLAB. There is a different process which is required to be followed in order to get the desired result.

The processes which are used in the project are as follows:-

SLLATEST

• Image Acquisition
• Edge detection
• Comparison of images
• Decision making

Let’s have a look at the algorithms.

Image Acquisition

In this process, we will scan the clear image of the fingers. If the fingerprints of anyone has faded the MATLAB feature will amplify the dots which are there on the fingers. The image will be scanned in JPG format.

Edge detection

The edge of an image is also confirmed to where the image will scan and manipulated. For that, we have to find the difference between corresponding pixels of the fingerprints. This is done by finding the gradient factor. The MATLAB is well suited for this kind of mathematical operations. 

Comparison of Images

In this process, we will be comparing the images with the save data. There is a false accept rate and false reject rate. The false accept rate will be calculated through the mathematical operation. The operation again is done with the help of extensive features of MATLAB. 

Decision Making

Here it is the most important step for the project. The decision is made on comparing the data with that of saved one to decide which fingerprints are those. We have to adhere to a number of factors if we wish to find the accurate result of that fingerprint. 

Conclusion

In this MATLAB project, we will learn more about pattern recognition. For this project, the person must require some prior knowledge about MATLAB. There is also a need for correct algorithms on which the project will work step by step accurately. The results are checked extensively to make the project correct and accurate. Poor quality image is the one which possesses a problem to the project but with the help of MATLAB and Simulink, we will able to identify the fingerprints correctly. 

SLDYK
Kit required to develop Fingerprint recognition algorithm using phase-based image matching:

• MATLAB

Technologies you will learn by working on Fingerprint recognition algorithm using phase-based image matching:

• MATLAB
• Image processing

Any Questions?