1. Shital ghule.

2.  INTRODUCTION: This paper proposes an ATM security model that would combine a physical access card,a pin and electronic facial recognition. It encloses the information regarding the ‘ image processing’. And discussed one of the major application of image processing ‘biometrics’. Biometrics technology turns your body in to your password. We will discuss various biometric techniques like finger scan, retina scan, facial scan, hand scan etc.. Face recognition technology may solve the problem since a face is connected to its owner making it impenetrable system.

3. The present generation security issue is considered the basic TCP/IP encryptions and other factors that are provided by the network. But there was lack of consistent identification of individuals, then the newly developed technology Biometrics, came in to picture.

4. Biometrics can be defined as recognizing and identifying a person based on physiological or behavioral characteristics. Biometrics can be used to prevent unauthorized access to ATM’s, smart cards, desktop PC’s workstations, cellular phones, home security systems, door locks, etc.

5.  AUTOMATED TELLER MACHINE:  An automated teller machine (ATM) is a computerized telecommunications device that provides the customers of a financial institution with access to financial transactions in a public space without the need for a human clerk or bank teller. On most modern ATMs, the customer is identified by inserting a plastic ATM card with a magnetic stripe or a plastic smartcard with a chip, that contains a unique card number and some security information, such as an expiration date. Security is provided by the customer entering a personal identification number (PIN).

6.  BIOMETRICS:  A biometric is a unique, measurable characteristic of a human being that can be used to automatically recognize an individual or verify an individual’s identity. Biometrics can measure both physiological and behavioral characteristics. Physiological biometrics -based on measurements and data derived from direct measurement of a part of the human body. Behavioral biometrics -based on measurements and data derived from an action.

8.  In biometrics a series of steps are followed to get the aimed goal, the steps are as shown in the figure below : Sensor : A sensor collects data and converts the information to a digital format. Signal processing algorithms : This is where quality control activities and development of the template takes place. Data Storage : Keeps information that new biometric templates will be compared to. Matching algorithm : Compares the new template to other templates in the data storage. Decision process: Uses the results from the matching component to make a system level decision.

9. Classification of biometrics

10. The two categories of biometric techniques are:- The physiological based techniques, which measure the physiological characteristics of a person. These include fingerprint verification, iris analysis, facial analysis, hand geometry-vein patterns, ear recognition, odor detection and DNA pattern analysis. The behavioral based techniques, which measure the behavior of a person. These include hand written signature verification and speech analysis.

11.  1 Finger scan: Finger-scan biometrics is base on the distinctive characteristics of the human fingerprint. Fingerprints are used in forensic applications: large- scale, one-to- many searches on databases of up to millions of fingerprints.

12. 2 Retina scan: Retina scan requires the user to situate his or her eye with ½ inch of the capture device and hold still while the reader ascertains the patterns. Retina scan is designed to use in military facilities, logical security applications such as network access or PC logic

13.  IMPLEMENTATION OF FACE RECOGNITION TECHNOLOGY:  IMPLEMENTATION OF FACE RECOGNITION TECHNOLOGY The implementation of face recognition technology includes the following four stages : Data acquisition Input processing Face image classification Decision making

14.  DATA ACQUISITION:  DATA ACQUISITION The input can be recorded video of the speaker or a still image. A sample of 1 sec duration consists of a 25 frame video sequence. More than one camera can be used to produce a 3D representation of the face and to protect against the usage of photographs to gain unauthorized access.

15.  INPUT PROCESSING:  INPUT PROCESSING A pre-processing module locates the eye position and takes care of the surrounding lighting condition and colour variance. First the presence of faces or face in a scene must be detected. Once the face is detected, it must be localized and Normalization process may be required to bring the dimensions of the live facial sample in alignment with the one on the template.

16.  FACE IMAGE CLASSIFICATION:  FACE IMAGE CLASSIFICATION The appearance of the face can change considerably during speech and due to facial expressions. In particular the mouth is subjected to fundamental changes but is also very important source for discriminating faces. So an approach to person’s recognition is developed based on patio- temporal modeling of features extracted from talking face. Models are trained specific to a person’s speech articulate and the way that the person speaks.

17.  DECISION MAKING:  DECISION MAKING Face recognition starts with a picture, attempting to find a person in the image.The face recognition system locates the head and finally the eyes of the individual. A matrix is then developed based on the characteristics of the Individual’s face. The method of defining the matrix varies according to the algorithm This matrix is then compared to matrices that are in a database and a similarity score is generated for each comparison

19.  1.A major problem with biometrics is how and where to store the user’s template. Its storage introduces privacy concerns. On the other hand, storing the template on a smart card enhances individual privacy and increases protection from attack, because individual users control their own templates.  2. Inside the eye is a very delicate area and so, many people are very hesitating to use laser eye device.

20.  3. Two primary causes of errors affect biometric data:- Time and Environmental conditions. TIME:- Biometrics may change as an individual ages. ENVIRONMENTAL:- Environmental conditions may either after the biometric directly (for example, if a finger is cut and scarred) or interfere with the data collection (for instance, background noise when using a voice biometric).

22.  Biometric technology is one area that no segment of the IT industry can afford to ignore, biometrics provides security benefits across the spectrum, from IT vendors to end users, and from security system developers to security system users. All these industry sectors must evaluate the costs and benefits of implementing such security measures.

23.  CONCLUSION:  CONCLUSION With new improved techniques like ARTIFICIAL INTELLIGENCE security margin can be increased from simple 60-75% to 80- 100% We thus develop an ATM model that is more reliable in providing security by using facial recognition software. By keeping the time elapsed in the verification process to a negligible amount we even try to maintain the efficiency of this ATM system to a greater degree making it faster and impenetrable.