CREDIT CARD TRANSACTION WITH FACE RECOGNITION
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CREDIT CARD TRANSACTION WITH FACE RECOGNITION

1Payal Sahare , 2Rohini Khobragade , 3Sachi Ambade , 4Samiksha Deshmukh , 5Dr. S M Malode
1,2,3,4BE Student, 5Assistant Professor, Computer Technology, K. D. K. College of Engineering,
Nagpur, Maharashtra, India

Abstract :

currently a days the net group action ar involved concerning the protection . this is often in the main because of the hacking of word or OTP’s and PIN code by the hacker . This paper proposes a technique for mastercard system employed in group action system which is able to integrate with he face detection . the matter faced by mastercard users is ton of privacy problems. this might usually occur once users provide their mastercard numbers to unfamilier indivisuals or once cards ar lost. Our answer proposes a way by that the image clicked by victimization digital camera throughout the registration method image captured notice the face and with feature extraction face hold on into the extraction face hold on into the info . At the time of payment created by the user on E-commerce portal are going to be compared to the feature from the info of the several user. Face feature from the info of the several user. Face options extracted from the photographs hold on in info. Our goal to check the similarity of faces embedded within the mastercard and several user.

Key Words : digital camera , group action, Verification , Face recognization , image process .

1 .INTRODUCTION

Nowadays , credit cards ar used worldwide. Credit cards ar face turning into the foremost common payment methodology of massive purchasers. folks use mastercard for on-line group action in looking malls . mastercard fraud is turning into the most important risk in mastercard group action . Credit cards and therefore the pin codes of the mastercard is purloined or lost . The planned answer offers a secure methodology for mastercard authentication victimization native binary pattern algorithmic rule . Face recognition technique . we’ve got enforced concepts for “Credit Card Authentication” supported automatic face recognition. The applications includes face recognization that saves time and eliminates possibilities of mastercard lost or purloined . Face recognition has been the earliest of the foremost fool proof ways in human detection . The automatic face recognition method is divided into 2 main categories: process before detection wherever face detection and alignment present itself and later recognition occur through feature extraction and matching .

1.1 Purpose of image process : The purpose of image process is split into following teams .

  1. Visualization – Observe the article that aren’t visible within the pictures
  2. .Image sharping and restoration – to form a much better image within the dataset.
  3. Image retrival – rummage around for the image of interest for pictures.
  4. Measurement of pattern – Measures varied objects in a picture for coaching purpose.
  5. Image Recognition – determine the objects in a picture and recognition the photographs or faces.

2. RELETED WORK

The mastercard group action could be an important application wherever the information given by the assorted forms of user is copied and accessed over the network and that they ar deleted that is a major downside within the world. The digital image process which will secure the mastercard system by victimization face recognition and face detection of a user for security purpose . Nowadays , Face recognition could be a each difficult and vital recognition technique during a day to day activity . Among all the biometric techniques like finger printing the face recognition approach possesses mist advantage, that is its user-friendliness. A face recognition , factors that will most have an effect on the performance of the recognizer. Face recognition is one in all the few biometric methodology or technique that possess the deserves of each high accuracy and low aggressiveness. The that means of Face recognition system, external body part options that use to spot the face , extract options, matches face , face, face recognition varieties together with 2 – dimentional system [2D] and three- dimentional system [3D] structure.

3.EXISTING SYSTEM :

The folks having the proper access to get something with a worth for the specified things and shopping for that merchandise. the primary charge card was issued within the London 1967. Payment cards with magnetic strips appeared in 1971, chip cards ar made-up in 1974. All the time banks sought-after to guard saving of their purchasers . a private number [PINs] ar typically employed in conjuction with usernames or passwords.

Advantages :

  1. Attack by key lumberman isn’t potential .
  2. Attack by brute force is extremely tough.

Disadvantages :

  1. Pin code will get purloined .
  2. It may well be forgotten.

3 .PROPOSED SYSTEM :

we’ve got 2 modules of implementation .

1 admin module :

The entire application is handled by the administrator. the complete details of the user is seen by him . All the small print like data delete , a read is done by the administrator Admin is that the main World Health Organization handles the entire administration method . Admin module permits supervisor to line up backend of the system and perform basic system configuration a part of the admin setup is users management that permits users to be setup with determinable access level / roles , access to the only or multiple branches . admin manifest the users group action by approving it.

2user module :

The user module permits users to register , login , logout. during this module user initial have to be compelled to register himself by giving complete details . when filling complete details he have to be compelled to provide the face so as to register his/her image onto the info Then whereas doing the group action face should be manifest for productive group action.

Fig. 3.1

4 . EXPERIMENTAL RESULTS :

Fig. 4.1
Fig. 4.2
Fig. 4.3
Fig. 4.4
Fig. 4.5

5 . CONCLUSION :

As the technology grows day to day, there ar numerous changes happening throughout entire system and significantly security for every element is critical. during this paper , the review of various automatic face recognition techniques is given. the various technique like linear Binary Pattern, Eigenfaces, Fisherfaces is explained . we tend to conjointly given the study of assorted work conducted by completely different researchers.

6 . REFERENCES :

  1. Anshul Singh, Devesh Narayan. (2012), ‘A Survey on Hidden Markov Model for Credit Card Fraud Detection’, (IJEAT) ISSN: 2249 – 8958, Volume-1, Issue-Ant´onio Miguel Louren¸co. (2009), “Techniques for keypoint detection and matching between endoscopic images”.
  2. Avinash Ingole, Dr. R. C. Thool. (2013), “Credit Card Fraud Detection Using Hidden Markov Model and Its Performance”, ijarcsse, Volume 3, Issue 6, pp. 626-632
  3. Clifton phua, Vincent Lee, Kate Smith & Ross Gayler. (2010), “A Comprehensive Survey of Data Mining-based Fraud Detection Research”
  4. D. Madhu Babu, M. Bhagyasri, K. Lahari, CH. Madhuri, G. Pushpa Kumari. (2014), “Image Based Fraud Prevention”, (IJCSIT), Vol. 5 (1), pp.728-731
  5. Dipti Deodhare, NNR Ranga Suri R. Amit. (2005), “Preprocessing and Image Enhancement Algorithms for a Form-based Intelligent Character Recognition System”, IJCSA, Vol. II, No. II, pp.131 – 144
  6. Dong ping, Tian. (2013), “A Review on Image Feature Extraction and Representation Techniques”, IJMUE, Vol. 8, No. 4, pp.385-395
  7. https://www.jumio.com/2011/07/jumio-turns webcam-into-credit-card-reader/
  8. ] http://www.marketcalls.in/credit-cards/the history-of-credit-cards.html
  9. http://wwwen.uni.lu/snt/research/research_proj ects2/prevention_of_fraud_by_pattern_detectio n_in_credit_card_transaction
  10. Khyati Chaudhary, Jyoti Yadav Bhawna Mallick. (2012), “A review of Fraud Detection Techniques: Credit Card”, IJCA, Vol. 45, No. 1, pp.39-44
  11. Kumar.G. (2014), “A Detailed Review of Feature Extraction in Image Processing Systems”, ACCT, pp.5 – 12
  12. Mark S. Nixon, Alberto S. Aguado. (2008), “Feature Extraction and Image Processing”, ISBN 0 7506 5078 8
  13. Rashmi G.Dukhi. (2011), “Soft Computing Tools in Credit card fraud & Detection”, ijetae.com, ISSN 2250-2459, Volume 1, Issue 2, pp. 60-64
  14. Vinay Hiremath, Ashwini Mayakar. (2012), “FACE RECOGNITION USING EIGENFACE APPROACH”

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