FINGER RECOGNITION USING NEURAL NETWORKS

Project Title

FINGER RECOGNITION USING NEURAL NETWORKS

Project Area of Specialization Artificial IntelligenceProject Summary

The use of fingerprint in biometric identification has been the most widely used authentication system. The uniqueness of the fingerprint for every human provides us with all we need for faultless identification. However, during the fingerprint scanning process, the image generated by the scanner may be slightly different during each scan. This paper puts the implementation of Artificial Neural Networks to provide an efficient matching algorithm for fingerprint authentication. Using the Back-Propagation technique, the algorithm works to match twelve fingerprint parameters and relate them to a unique number provided for each authorized user. Upon matching, the algorithm returns the best match for the given fingerprint parameters

Project Objectives

To study the importance of fingerprint recognition in the current biometric
authentication systems.
· To determine the factors affecting the fingerprint recognition system.
· To investigate the factors affecting the fingerprint recognition rate.
· To develop an effective algorithm for fingerprint recognition.
· To collect standard database of fingerprints.
· To develop MATLAB code for the effective fingerprint       recognition algorithm.
· To determine the percentage of recognition from the developed code.
· To compare the recognition percentage with previous recognition rate of other
researchers.
· To discuss the results with experts/guide.
 

Project Implementation Method

All process of recognition of fingerprint with artificial neural network given below Fundamental Steps of Fingerprint Recognition System Fingerprint Image: A fingerprint is the feature pattern of one finger. Each person has his own fingerprints with the permanent uniqueness. Due to the uniqueness and permanence of fingerprints, they are among the most reliable human characteristics that can be used for personal identification. Image Acquisition: A number of methods are used to acquire fingerprints. Among them, the inked impression method remains the most popular one. Inkless fingerprint scanners are also present eliminating the intermediate digitization process. Fingerprint quality is very important since it affects directly the minutiae extraction algorithm. The size of the scanned fingerprints that are used in this research is 188x240 pixels. The images are taken in this size in order to ease the computational burden. Fingerprint Image Processing: Processing of fingerprint image is necessary to: (i) improve the clarity of ridge structures of fingerprint images (ii) maintain their integrity, (iii) avoid introduction of spurious structures or artifacts, and (iv) retain the connectivity of the ridges while maintaining separation between ridges. Fingerprint image processing operations are image enhancement, image normalization and image binarazation.

Benefits of the Project Access and Timekeeping

Most fingerprint scanning systems verify a person's identity to ensure they have permission to access a secure area. Many employers also use fingerprint scanning systems to confirm when an employee arrives or leaves work. Since time theft can cost the company a large amount of money, using a fingerprint security system to track employee attendance can prevent another coworker from clocking someone in or out. This results in more accurate time logs and fewer mistakes.

Reliability

Fingerprint scanning systems provide a reliable way to track employees and you don't need to worry about storing extra data, since the system only requires a fingerprint. With a fingerprint-based system, employees don't need to worry about keeping cards or passwords safe. Fingerprint-based systems provide the ability to detect an individual out of millions of fingerprints accurately.

Security

Most other security systems have a higher risk of breaches caused by employee error. Someone can take advantage of a badge carelessly left behind to access a forbidden area, or a skilled worker may be locked out of his work area if he left his work badge at home. Fingerprint-based systems provide additional security, since criminals can't easily fake a fingerprint, fingerprints can't get misplaced and employees can't forget to bring their fingerprint to work.

Technical Details of Final Deliverable

Human fingerprints are rich in details which is known as minutiae, which can be used as identification marks for fingerprint verification. Our term project is to study on fingerprint recognition system based on minutia based matching which is quiet frequently used in various fingerprint algorithms and techniques. The approach of this project involves how the minutia points are extracted from the fingerprint images and after that between two fingerprints we are performing the fingerprint matching. Image enhancement, image segmentation, minutia extraction and minutia matching these stages are the main themes of our project. This project will be incoded in python.

Final Deliverable of the Project Hardware SystemType of Industry IT Technologies Artificial Intelligence(AI)Sustainable Development Goals Peace and Justice Strong InstitutionsRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	60
sensor	Equipment	4	15	60