Fingerprints Recognition using

Neural Network

Presented By:GURJANT SINGH SANDHU (328)PRANJAL SINGH (333)

FingerprintsA fingerprint in its narrow sense is an impression left by the friction ridges of a human finger.

Their pattern is permanent and unchangeable on each finger during the whole life time of an individual.

The probability that fingerprints of two individual are alike is about 1 in 1.9×1015.

According to FBI the accuracy and reliability of fingerprint scans are correct 99.8% of the time.

Fingerprint Pattern

Pattern recognition System

Image Acquisition Converting a scene into an array of numbers that can be manipulated by a computer.Edge Detection and Thinning These are the part of preprocessing step which involves removing noise, enhancing the picture and, if necessary, segmenting the image into meaningful regions.

Image Acquisition

Edge Detection Thinning Feature

Extractor Classifier

Pattern recognition System

Feature extraction The image is represented by a set of numerical “features” to remove redundancy from data and reduce its dimensions.Classification Class label is assigned to the image by examining its extracted features and comparing them with the class that it has already learned.

Image Acquisition

Edge Detection Thinning Feature

Extractor Classifier

Why use Neural Network? A neural network consists of an

interconnected group of artificial neurons, and it processes information and help us to find solution.

There is no need to program Neural Network they learn with the examples.

Neural Networks offers significant speed advantage over conventional techniques.

Other ApplicationsCharacter Recognition The idea of character recognition has become very important as handheld devices like Palm Pilot are becoming increasingly popular.

Image Compression Neural networks can receive and process large amount of information at once, making them useful in image compression. With internet explosion and more and websites using more and more images, using neural networks for image compression is worth a look.

Other ApplicationsStock Market Prediction The day-to-day business of stock market is extremely complicated. Stock prices will go up or down is the result of many different factors. Since neural network can examine a lot of information, they can be used to predict stock prices.

Travelling Salesman Problem Neural network can solve the travelling salesman problem, but only to a certain degree of approximation.

Medicine, Security, and Loan Applications.

Preprocessing SystemThe first phase of the work is to

capture the fingerprints image and convert it into a digital representation of 512×512 by 256 grey levels.

The binary image is further enhanced by a thinning algorithm which reduces the image ridges to a skeletal structure.

Preprocessing SystemAfter obtaining the binary form of the

fingerprint image, there may be some irregularities caused by skinfolds and spreading of ink due to finger pressure, and so on…

The remedy to this problem is smoothing to fill holes, delete unnecessary points, removing noisy points and filling necessary missing points.

Application of fingerprint Recognition

The fingerprint recognition system can be easily embedded in any system. It is used in-◦ Recognition of criminals in law enforcement.◦ Used in providing security to cars, lockers, banks,

shops.◦ To differentiate between persons.◦ To count the individuals.◦ Drug detection.

CriticismDespite the widespread acceptance of fingerprint

evidence, many question its worth due to a significant amount of identification mistakes. There is a question of its reliability and accuracy.

For example, in 2000, an individual was arrested for murder and was told by police that fingerprint experts matched his fingerprints to those found at the crime scene. The individual's attorney hired his own fingerprint experts, two former FBI examiners, who determined that absolutely no positive identification took place. After some post-incarceration legal wrangling, this evidence was deemed sufficient for an acquittal.

ConclusionFor centuries fingerprints have been one of

the most highly used methods for human recognition; automated biometric system have only been available in recent years.

The advancement of technology have led to next generation of fingerprint recognition devices which are highly reliable and accurate.

Fingerprints have a broad acceptance with the general public, law enforcement and the forensic science community.

Hence, they will continue to be used for human recognition and for new systems that require a reliable biometric.

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