Advanced ATM System

Advanced ATM System

Divya Vaghela1, Janisha Kumar2, Preksha Jain3, Rashmi Iyengar4, Prof. Niranjan Samudre5

BE Student1234, Assistant Professor 5 Dept of Electronics Engineering 12345 Atharva college of engineering12345 Mumbai, India12345

Abstract Biometric authentication has been proven to be of high accuracy in user identification. To achieve more accurate identi- fication it is better to use which characterizes an individual. The various biometric features that may be used for authentication includes fingerprint, palm print, handprint, face recognition, speech recognition & eye biometrics out of which fingerprint has higher accuracy as compared to others mentioned. A fingerprint is a combined formation of ridges and

valleys. This system recognizes fingerprint to access bank ac- counts of only those individuals whose fingerprint have been reg- istered. In case of battery drain or a mishap like complete power failure, stored fingerprints are retained. A prototype of ATM sys- tem based on a microcontroller using fingerprint sensor module is implemented. The programming platforms that can be used are MySQL and Visual Studio. This can be implemented as a hard- ware project as well as desktop application.

Keywords ATM, Biometrics, Fingerprint, Authentication., Secu- rity.

1. INTRODUCTION

   Based on a physiological or behavioral characteristic it is pos- sible to recognize an individual using Biometric techniques. It can be implemented to improve the security of financial trans- actions and for personal uses. Utilizing biometric sciences, we can identify/verify distinctive features of an individual. The various features used are face, fingerprints, hand geometry, handwriting, iris, retina, vein and voice. Amongst the various biometric techniques trending, finger-scan is the most efficient and feasible technology therefore the commonly used one as well. The transactions of money play an important role in the present society. ATMs, Debit cards and Credit cards are mainly used for transactions. Authentication in ATM system is done using ATM cards and Personal Identification Num- ber(PIN). Nowadays ATM cards can be cloned easily by in- truders, therefore authentication provided by conventional methods are not highly secure. The fingerprints of customers can be used instead of traditional ATM card to overcome this disadvantage, as fingerprint of every individual is unique and unchangeable.

2. LITERATURE SURVEY

   The primary aim of this project is to convolve security and bi- ometric technology to produce the secure system.The Hand- book of Fingerprint Recognition helps us to understand the science of automatically identifying individuals based on their physiological or behavior characteristics [2] The Biometrics: Advanced Identity Verification helps us to understand fin- gerprint matching techniques. [4] The Biometrics: Identity Verification in a Networked World helps us to understand the benefits over traditional authentication approaches [3] The

   journal Introduction to Biometrics helps us to understand use of fingerprint scanners to authentic computer users [1]

3. IMAGE ENHANCEMENT

   1. Contrast Stretching

      Contrast stretching (often called normalization) is a simple im- age enhancement technique that attempts to improve the con- trast in an image by `stretching' the range of intensity values it contains to span the desired range of values, e.g. the full range of pixel values that the image type concerned allows. It differs from the more sophisticated histogram equalization in that it can only apply a linear scaling function to the image pixel val- ues. As a result, the `enhancement' is less harsh. Most imple- mentations accept a gray level image as input and produce an- other gray level image as output.

   2. Histogram Equalization

      This method is basically incorporated to increase the global contrast of many images, whenever the usable data of the im- age is represented by similar contrast values. Due to this ad- justment, the intensities can be better distributed on the histo- gram. This also allows for areas of lesser local contrast to gain a considerably higher contrast. This can be accomplished by effectively spreading out the most frequent intensity values.

4. WORKING Steps involved are as follows:

   • User will login to the system using his fingerprint.

   • The user has to scan the finger and add a pin in order to do transactions.

   • Withdrawal of cash is to be done by entering the amount user wants to withdraw.

   • The user can transfer cash to other accounts by enter- ing the account number he wants to transfer.

   • Balance, as well as last five transactions, can be viewed which is available in his/her respective ac- count.

5. FINGER SCAN TECHNOLOGY Stages involved for fingerprint enhancement are as follows:

   • There are five stages involved in finger-scan verification and identification. Fingerprint (FP) image acquisition, im- age processing, and location of distinctive characteristics, template creation and template matching.

     Fig 1: Block diagram for the fingerscan process.

     • A scanner takes a mathematical snapshot of a user's unique biological traits. This snapshot is saved in a fingerprint database as a minutiae file. The first chal- lenge facing a finger-scanning system is to acquire a high-quality image of a fingerprint. The standard for forensic-quality fingerprinting is images of 500 dots per inch (DPI).

     • Image acquisition can be a major challenge for finger- scan developers since the quality of print differs from person to person and from finger to finger. Some pop- ulations are more likely than others to have faint or difficult-to-acquire fingerprints, whether due to wear or tear or physiological traits. Taking an image in the cold weather also can have an effect.

     • Oils in the finger help produce a better print. In cold weather, these oils naturally dry up. Pressing harder on the platen (the surface on which the finger is placed, also known as a scanner) can help in this case. Image processing is the process of converting the fin- ger image into a usable format. This results in a series of thick black ridges (the raised part of the finger- print) contrasted to white valleys.

     • At this stage, image features are detected and en- hanced for verification against the stored minutia file.

     • Image enhancement is used to reduce any distortion of the fingerprint caused by dirt, cuts, scars, sweat and dry skin.

6. ADVANTAGES AND LIMITATIONS

   The size of the memory required to store the biometric tem- plate is fairly small. Fingerprint based ATM System is more secure than ATM card. The user can make a transaction using his fingerprint anywhere and at any time he need not have to carry ATM card, but There is a fraction of the population that is unable to be enrolled. There are certain ethnic groups that have lower quality fingerprints than the general populations. Testing has shown that elderly populations, manual laborers, and some Asian populations are more difficult to be enrolled in some finger-scanning systems. If the User finger pattern has some cut or got damaged the system might not recognize the user.

7. APPLICATIONS

   It can be used in Banking & Finance, Membership Verification ATM, Transaction / Check Deposit ATM and Self Service ATM.

8. CONCLUSION

Finger-scan technology is proven and capable of igh levels of accuracy. Identical matches are nearly impossible since finger- prints contain a large amount of information making it unlikely that two fingerprints would be identical. The design of finger- print image enhancement Fingerprint recognition module is an extremely important part of the system, the high-quality im- ages was the major factors of influencing the performance of the system.

ACKNOWLEDGEMENT

We would like to express our sincere thanks to our guide Mr. Niranjan Samudre for taking time from his busy schedule to provide us with a great deal of help, support and encouraged us to work diligently on every aspect of our project. His views have always been equitable providing a perfect balance be- tween encouragement and constructive criticism. His tips and suggestions helped us to decide the correct approach to the project. We are thankful to our college Principal Dr. S. P. Kal- lurkar, ELEX HOD Mrs. Disha Bhosale, and all staff members of Electronics department who have provided us variousfacil- ities and have guided us whenever required. We attempted to find help from a variety of individuals atvarious stages of the project. We would like to thank everyone for their guidance. Finally, we would like to thank our parents and our friends for constantly supporting and encouraging our efforts.

REFERENCES

1. The Biometric Consortium, Introduction to Biomet- rics,(http://www.biometrics.org), 2006.

2. D. Maltoni, D. Maio, A.K. Jain, and S. Prabhakar, Hand- book of Fingerprint Recognition, Springer, London, 2009.

3. Samir Nanavati, Michael Thieme, and Raj Nanavati, Bi- ometrics: Identity Verification in a Networked World, John Wiley & Sons, 2002.

4. Julian Ashbourn, Biometrics: Advanced Identity Verifi- cation, Springer-Verlag, London, 2002.

5. Edmund Spinella, Biometric Scanning Technologies: Finger, Facial and Retinal Scanning, SANS Institute, San Francisco, CA, 2003.

6. Peatman, John B., Design with PIC Microcontrollers, Pearson Education, India, 1998.

7. Microchip Technology Inc., PIC16F87XA data sheet, DS39582C, 2013.

8. Lin Hong, Wan Yifei, Anil Jain. Fingerprint image en- hancement: algorithm and performance evaluation[J]. IEEE Transactions on Pattern Analysis and Machine in- telligence. 1998,20(8): 777-789.