Category: CSE Seminar Topics

Fingerprint processing

Fingerprints are not compared and also not stored in the database as bitmap images. Fingerprint matching techniques can be placed into two categories: minutiae-based and correlation based. Minutiae points are first found and then mapped to the relative index of the finger in minutiae-based technique.           

Loop:

The most common type of fingerprint patterns is loop and it account almost 65% of the matches and is as shown below.        

Arch:

The arch pattern is a more open curve than the loop. There are two different models of these particular arch patterns: they are the “plain arch and tended arch patterns” 

Whorl: 

“This particular pattern occurs almost 30% fingerprints and are defined by atleast one ridge that composes a complete circle and is as shown below” 

It is not always sure that fingerprint ridges are straight and continuous 

always. They can be broken, forked and changed directionally. The points where the ridges end or broken are called minutiae points and these points are the main key for unique identification. Ridge endings and ridge bifurcations are the two most important types of ridge points and are as shown below                  

The most important factor the decision speed mainly depends on  few items like the level of security implemented and answers that were delivered in the sense negative answers will affect the speed than the positive answers any more. The speed and the accuracy algorithms are no way dependent on each other. The minutiae found on many fingerprint samples are stored for future comparison studies. Encoding and other compression techniques are also applied on minutiae samples found. In general the typical and traditional formal size of these particular master templates would be around  between 24 bytes and one kilobyte. A very huge set of these desired data is stored in the fingerprints captured. Due to the heavy level of data that is present in any single fingerprint the probability of resulting a wrong match is always less and can be reduced to a very small fraction. These fingerprint technologies can also be targeted and more better ways can be implemented to achieve these targets on a very large databases.

To obtain the accurate results from the fingerprints, there are some pre-processor techniques and steps to be followed and few of them are as below

Evaluating Biometrics

Bio-metric industry has tremendous growth since 3 to 5 years. There was a call for more bio-metric application after the collapse of twin towers on sep 11^th. Those, however, seem to be reluctant to invest in a technology that is still emerging and therefore features a bewildering diversity of products and companies. As a recent article in the Washington Business Journal brought it to the point, “bio-metrics is the next evolution in security, but it’s a very fragmented industry, with lots of companies trying different things” 

Metrics and performance criteria 

It’s always challenging to any bio-metric or traditional authentication systems to provide more secure authentication, identification and verification process. There are lot of mechanisms by which the performance of any system is monitored. All these values should be tracked in a finniest manner irrespective of the methodologies used while capturing the results.

All most all the bio-metric tools uses few buzz words to identify the measuring the factors of the performance. For example, a renowned vendor of fingerprint sensors claims on his website that his “sensor achieved 0.0% false acceptance and 0.0% false rejection rates”. Like this there are lot of attractive and good looking technical standards and measurements are set to measure the performance of the bio-metric systems. There are many metric that we used to measure the performance of the bio-metric system and three among them are as listed below 

False Match Rates (FMR) 

False Match Rate is the probability that the respective system will match the current user verification template with another user verification and enrollment template. It can be understood as the likelihood of an impostor being recognized as a legitimate user. This is the most frequently found error rate and can be handled very critically with any knowledge on the error rates. 

False Non Match Rate (FNMR) 

False Non Match Rate is the probability that a particular user verification template is not matched with the same users enrollment template. Heavy  false match rates could always lead to low or zero productivity or user frustration and may be not that critical as False Match Rate. 

Failure-to-Enroll Rate (FTE) 

Failure-to-Enroll Rate is the probability that the system will not

be able to extract distinctive, consistent and replaceable characteristics from the sample presented during the enrollment process, i.e. this is the likelihood of the system being unable to create an enrollment template for a new user. The affect of this could in the behavioral side rather than physical side. 

All the above Failure rates will impact the system in one or more ways and this affect is depend on the number of iterations worked on the failure rates. The most predominant among all the three key failures are are False Non Match Rate and Failure-to-Enroll. These two plays a very important role in determining the performance of the bio-metric system. In the ideal cases at maximum only three attempts should be done for any metrics and it’s affect operations.

Facial recognition 

Facial recognition is one of the widely and most commonly used biometric application and this can also considered as the natural means of identification technique that were in the market. Any high quality camera with capability capture the images with a very high resolution can be used to capture the images of human faces and also a scanned copy of the image can also be used for this facial recognition process. More accurate results can be produced by the better image that is captured either by a camera or we can use scan copy. Gray-scale information is the primary input for facial recognition systems.

The colors of the final image captured are only taken in to consideration for identifying the face in the entire picture that was captured. Quality of the camera plays a very important role in the lightening conditions. A poor light condition does not make sense to identify an individual facial features and thus a proper steps need to be taken to avoid the poor camera light if there exists any thing. Now-a-days the most advanced infrared cameras can be used for these facial recognition systems. 

For a better picture quality the desired user should be at a pre-defined distance from the particular camera, so that the facial recognition system can get an extra quality input for it’s internal processing. Locating the face with in the entire image would be the very first task of any facial recognition systems and the respective facial characteristics are captured. After locating the face in the image, the system focus on eyes of the face as shown in the below image

Facial metrics mainly depends on measurement of specific features of face like eyes, nose and mouth and also distance between them is also considered. Now-a-days a more sophisticated method for recognizing the face has been developed and widely used since three years. As per this method the faces are categorized based on the angle of fit and with a “fixed set of 150 master eigenfaces. In this process every face is assigned a degree of fit to each of the 150 master eigenfaces and only the 40 template eigenfaces with the highest degree of fit are necessary to reconstruct the face with the accuracy of 99%.” 

A computer software will take care of the image processing and calculates the degree of fit. A lot of intelligent computing power is required to process this technique and assembling a stand alone face recognition system may not serve the purpose. There were lot of efforts now a days to build a sophisticated and chip based embedded system that can be used for facial recognition system which holds a special instruction set.

The accuracy of the computer software is not that ideal and has lot of disadvantages that can be discussed and still there is a lot of potential scope of improvising the algorithms being used as of now. The current software in place may not recognize the face or may identify the face at a wrong place. If the eyes are positioned at the exact place then much better results can be achieved.

The face recognition can be re-sizeable up to an extent like 150X100 points. This normalized shape of the face is called canonical image and the size of this template can be in the range of 3 to 5 KB and is as shown below

Retina Scan 

Retina scan can be considered as one of the important biometric scanning methodologies. This particular process of scanning the retina is mainly based on the vessel pattern of the blood that resides inside the retina of any eye. “The first retinal scanning systems were launched by EyeDentify in 1985”. Infra red light source influences the retina apart from the normal visualization. Blood vessels present inside the retina of eye absorbs the infrared radiations very quickly and the tissue is also affected by this absorption. The retina blood vessel pattern is captured as an image and special characteristic points are analyzed. Below image shows a typical retina patterns 

Intrusiveness can be considered as the main drawback of the retina scanning process. The way the retina scan was obtained can be considered as not safe and is much dangerous when suggested. The cornea of eye is directly affected by the laser light during the retina scan and this process is not that easy to execute and requires a lot of skilled operations and instruction sequences. The volume of data produced by retinal scan is almost same as the fingerprint scan process and thus this scan process can be used both for identification and verification.

In the practice, however, the retina scanning is used mostly for verification. The size of the eye signature template is 96 bytes. Retina scan produces much more accurate results 

Because of it’s less user friendliness and expensive retina scan is not being used widely and is used rarely. This retina scan can be launched and implement in cases where there is a huge scope for security and user authentication. Retina scan systems are used in many U.S. prisons to verify the prisoners before they are released. Below figure shows a typical retinal scanner system that was used commonly

Why Use Biometrics? 

There are lot of advantage in using the biometric based applications. These are used to identify and authenticate many people for most secure gateways. It identifies a persona in many unsafe and preliminary conditions and recognizes you as you. Many important object like tokens, Id cards, ATM cards can be lost or being theft. Most secured identities like the passwords which can be easily forgotten and even in some cases they can be loosed or stolen across the network by different types of hackers around the internet.

           Now-a-days the most high end e-commerce and electronic world is making the end users to remember their personal identification proofs like passwords. These high secured requirements are also posing to create multiple passwords and authentication metrics like ATM pins, Personal authentication templates. Apart from all these authentication formats, now-a-days biometric based applications came in to the technical world for providing the end users a more secured and sophisticated methodologies for authentication process across the secured systems. 

Every biometric system has it’s own advantage and disadvantages and in ideal case there is no perfect biometric identification system. The main usage and success of any biometric system depends on it’s unique features that can not be compared with few others and it’s user friendliness. The process being followed by any biometric system should be quick and easy to implement the features provided it, such as having a picture taken by a video camera, speaking into a microphone, or touching a fingerprint scanner. Below figure shows a typical biometric applications

Types of Biometrics 

Finger prints: 

For an individual the patterns of friction ridges and valleys on fingertip’s are unique. Fingerprints are unique for each finger and this uniqueness is followed in case of twins also. Finger print recognition devices are the most commercially available biometric tools for both desktops and laptops. Fingerprint systems are also used in identification tools. Many countries are ensuring that all the people should enroll in the fingerprint systems in threat of fake applicants for many social activities. Recent surveys came up with a new result that “New York State has over 900,000 people enrolled in such a system”. 

Face recognition: 

Now-a-days identification of a person using face features has become the most widely used biometric application. The particular facial image is captured by few high end technologies and techniques where a less expensive camera and visible spectrum are combine used as a set to capture the images that will emmet the infrared patterns of the desired face objects. By using a wide range of cameras the visible portion of the face can be 

captured that are not affected by the change in time and also avoiding few typical and unconditional  features like hair and expressions of face. 

Iris recognition:         

The colored area that surrounds the pupil of eye is used as input for Iris recognition. The patterns of Iris are really tough and complicatedly unique. Video based acquisition system are used to capture the iris patterns. Iris recognition system and it’s technology works good for both identification and verification modes. In this particular case there is no mandatory condition that a physical coordination is required with the desired biometric machine that is being used across. This particular recognition system is widely used and practically demonstrated in many cases and could have greatly managed to give results that shows differences in different races and groups across the world. 

Hand and Finger geometry: 

Hand and Finger geometry are the well established personal identification methods and since twenty years hand recognition systems are available in the biometric market. The physical characteristics of  the finger or hand are required for personal authentication process. Typical feature of hand like length, width, height and surface area of hand can be considered for these traditional ways studying the biometrics. 

Signature verification: 

The speed, angle used to sign and the pressure applied by a particular person is used for this signature verification technology. This particular method of signature verification can be implemented in may online services 

like e-commerce and e-business suites, where there is a very high scope of security needed while doing many economical and financial transactions that occur online. Few example include online shopping, credit card acceptance systems also use these signature verification systems.

Biometrical is the process of identifying a person based on few intrinsic behaviors both physical and mental. In the latest trend of IT world, we can say that biometrics can be used a more secured form of identity and recognition access management and access control. It is also used to identify human groups. Characteristics of Biometrical can be classified in to two types as below

Physiological Biometrics 

Physiological Biometrical are related to the shape of the body. Few examples are fingerprints, face recognition and DNA.

A biometric system can be used for the following two modes

Verification 

The biometric proof that was captured is stored in a template form and can used in a similar way how a smart card, user name or ID number systems work and follows the same methodologies for the verification and authentication process.

 Identification

A particular sample of biometric template is taken and compared with many samples available in the huge biometric database. A biometric database contains all the pre-defined and enrolled templates. This comparison results positive results only when the template being compared is already available in the huge database, and if it does not match, this matching result will be the base for catching the wrong authenticated entity across the biometric system being implemented.

The process of using the biometric system for the first time is called enrollment. Individual information is stored during the enrollment process. Note that it is crucial that storage and retrieval of such systems themselves be secure if the biometric system is to be robust. Below is the basic block diagram of a typical biometric system.

Sensor is the interface between the system and real word and this is the one which acquires the actual data. Most of the times it is an image acquisition system, but it can change according to the characteristics desired.

The second block i.e pre-processing removes the unnecessary artifacts from sensor and performs normalization like removing the noise from the speech to improve the input from the sensor.

The main operation of third block is to extract the feature needs and we can say this step is the most important one as there is a large scope for extracting the exact features in an optimal and cost effective system. A typical template is created by a number of tools like vectors, and these vectors considers many characteristics of an image that was captured for the purpose of biometric study.

A template can be explained as simple blue print of the characteristics that were captured from the original source of image. Few typical elements of the this particular measurement of biometric samples are not considered in the comparison algorithm of the template being used, to decrease the size of the file and also to ensure that the enrollee is protected in all the possible ways.

Use for Biometrics        

A typical Biometric applications is not only used to study the human authentication process, but also can be used to study the character and behavior changes of animals too. A typical example for the same is , a biometric system can be implemented to trace the race of a horse and also there is common biometric system in place where the famous pedigree company uses to check whether any dogs are being imported illegally.

Evaluating Biometrics

Biometric industry is one of the main industries which is growing rapidly in the recent years .The necessity of this industry occurred when there was drastic incident which took place in USA on twin towers on sep11 made to think about this industry. but still many of the industrialists are unwilling to put in into this evolving technology due to this the industries are producing products which are unsatisfied this is proven by the recent article which is published byWashington Business Journal “biometrics is an industry which is disjointed, and is the next evolution in security, with many organizations trying variety of things”.

Metrics and performance criteria:

Since biometrics deals about security system it should be done with high concentration and demanding to offer different credentials, authentications and other conformations   to the biometric systems. Different type of mechanism delivers different results which is viewed .and the best part of these are processed for captured for solutions whatever may be the methodologies .these biometric tools   performance can be evaluated by few words this can be explained by example when a client of censoring fingerprints who displays in portal as “0.0%false avoiding rates” And some other full-fledged standards maintained and this can act as a performance evaluators in the biometric systems. But three are very crucial in evaluating these performances which are quoted below.

False Match Rates (FMR):

FMR gives the ratio when the current user identification is verified with another registered identification of the current underlying system. it can be taken as the fake being is identified as  rightful user. This is the common error occurred and it easily solved with minimum control on error rates.

False Non-Match Rate (FNMR):

FMR is statistic used to measure biometric performance. Similar to the False Reject Rate (FRR), this is done when particular identification is not matched with the other registeredtemplate and huge false rate results may give zero production and also leads to client depression. 

Failure-to-Enrol Rate (FTE):

The rate that attempts to create a template from an input is unsuccessful. This is most commonly caused by low quality inputs. Like expandable characteristics which is given during identification process. That means for new client system is unable to deliver the process it affects the mental nature than physical nature.

For every procedure mostly three trails should be done and all the metric rates will create a force in different ways and this relies on no of iterations done on these processes. FNMR and FTE play a key role in accessing the biometric   routines and hence these two are very important.

Several methods for generating cancellable biometrics have been proposed.

Conclusion:

All the above study indicates that the importance of biometrics is vast in the present day world and even it is clear that biometrics are playing a vital role in the daily routine of the human beings. In the present generation the usage of biometric systems for user authentication has become common. In providing security for the users from the fake users or hackers and attackers these biometric applications plays a lead character, that means the technology used is very important in proving required security for the end users. Because of the present society and with the usage of advanced technologies the frauds are also increased in advanced level.

These frauds can be addressed by using the biometric systems in a better way. Biometrics introduces better and sophisticated technologies that can provide good benefits for the users. There for day by day the importance and usage of biometric systems is increasing in the world. The popularity of biometrics is spreading in a wide range. Biometrics systems can secure data in a good manner and along with this even it can be worked in other areas where security is needed. The features of biometrics will become advanced in the coming generation due to the fastest establishment of advanced technologies in the world.