29-09-2016, 03:16 PM
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ABSTRACT
With the increase in technology threat to personal data and national security had also increased. The methods that were developed to secure important information from outside intervention were not up to safe mark .There was a need to introduce a technology that secures our data more efficiently from unlawful intervention .
Fujitsu has developed a palm vein pattern authentication technology that uses vascular patterns as personal identification data .Vein recognition technology is secure because the authentication data exists inside the body and is therefore very difficult to forge. It is highly accurate. This technology can be used in various fields like banking, hospitals, government offices, in passport issuing etc. Business growth will be achieved with these solutions by reducing the size of the palm vein sensor and shortening the authentication time.
Hand vein is a biometric modality that seems promising as it is acquired in Near Infrared light (NIR), which implies that skin variations and dirtiness are less sensible than in visible light. Moreover, the haemoglobin which flows in the veins is sensible to NIR light, this way allowing a good quality of acquisition of the hand veins. It is possible to use either the back of the hand or the hand palm. A recent study using back hand vein data and tested with 5 sessions per person and 50 persons showed promising results. The main problem of this database is the low resolution of the images (images at resolution
132x124 pixels).
The first commercialized products have been produced by Hitachi on the back and Fujitsu on the palm. They have been patented but only little information is available on them. These companies claim a very low FRR ( False Rejection Rate) at very low FAR (False Acceptance Rate) on a huge database – close to 0% on 140000 hands. Unfortunately at this moment, there is no public database allowing verifying these figures. In general, in the various papers present in the literature, after the acquisition phase, some matching
algorithms are used such as the Line segment Hausdorff Distance (LHD) method. The LHD method has good experiment results. But, the structure information of palm vein is not as clear as hand vein, so line-based feature is not a good choice for palm vein recognition. Matching based on minutiae analysis and Hausdorff distance (MHD) was used for hand vein recognition. Minutiae-like feature could also be extracted from palm vein pattern; however, the Hausdorff distance algorithm applied in minutiae analysis is sensitive to the geometrical transformation. Besides P2PM, LHD and MHD, all existing matching methods suffer from the problem of image rotation and shift. Therefore, it is necessary to develop a new matching method which can effectively solve this problem. This paper presents a new and efficient matching method by introducing the iterative closest point (ICP) algorithm into palm vein verification. The ICP algorithm was firstly proposed by Besl and McKay and it was originally used in the registering of three dimensional (3D) range images. It is also well suited to align two dimensional (2D) images. In the proposed method, we first extract vein information from the Region of Interest (ROI). When matching two ROIs, we use ICP to estimate the rotation R and translation T between them. Then we use the estimated R and T to correct the ROIs so as to reduce the rotation and shift variations. The refined alignment of ROIs can bring great benefit in the consequent palm vein verification. The detail of ICP algorithm is explained later in the report. This paper is about the palm vein technology, its applications, how this technology is applied in real time applications and the advantages of using this technology.
Chapter-1
INTRODUCTION TO BIOMETRICS
1.1 WHAT IS BIOMETRICS?
Automated measurement of Physiological and/or behavioral characteristics to determine or authenticate identity is known as Biometrics [5]. Three components of above definition will determine what is and what is not a biometric and also its different types and functionalities.
Let’s start with the First component of the definition: “Automated measurement”, which means no human intervention or involvement is required. Biometrics are automated in as much as the processes involved in sample acquisition, feature extraction, record retrieval, and algorithm-based matching are computerized or machine-based. Also the record retrieval and comparison against another measurement must take place in Real- Time. So for an instance, DNA sampling is NOT a biometric measurement because today it still requires human intervention and it’s NOT done in real time. The second component of the definition: “Physiological and/or behavioral characteristics”, determine the two main biometric categories: behavioral and physiological. The behavioral characteristics measure the movement of a user, when users walk, speak, type on a keyboard or sign their name. The physiological characteristics would be the physical human traits like fingerprints, hand shape, eyes and face, veins, etc., and the last component of the definition is “determine or authenticate identity”, which categorizes the two types of biometric functionalities[5]. The first type is identification systems or the systems that answer the question who am I? and determine the identity of a person. The second type is verification systems or systems that answer the question, am I who I claim to be? and authenticate a person.
An example of an Identification System using biometrics would be: You approach an ATM with NO card, NO claimed identity, NO PIN. The ATM scans your iris and determines who you are and gives you access to your money.
An example of a Verification System using biometrics would be: You approach an ATM and swipe a card or enter an account number. The ATM scans your iris and uses it as a password to authenticate you are the rightful owner of the card and therefore give you access to your money.
1.2 USAGE OF BIOMETRIC TECHNOLOGY MINIMIZES RISKS
The person, who has my office id card, can…
The person, who has my house key, can…
The person, who knows my password, can…
The person, who knows the pin number of my credit card, can…
The person, who is able to forge my signature, can…
The person, who steals my passport, can…
1.4 BIOMETRIC FEATURES
It becomes obsolete to beware passwords safely or to remember to all of them.
Abuse of stolen id cards and passports will be reduced enormously.
Abuse of stolen credit cards will be prevented.
Taking over foreign identities will be impossible.
Building access right to people without the right of admittance will be prevented.
Access to devices/computers will be not possible for persons without the right of admittance.
Unnecessary costs will be drastically reduced.
Level of common convenience and safety will grow.
1.5 DIFFERENT BIOMETRIC TECHNOLOGIES
Voice Print Technology
Finger/palm Print Technology
Face Recognition Technology
Iris Scan Technology
Retina Scan Technology
Ear shape recognition Technology
Dynamic Signature Recognition (DSR)
Typing Pattern Technology
Gait Recognition Technology
Palm Vein Technology
THE BASIS OF PALM VEIN TECHNOLOGY
Every individual have unique pattern of Palm veins, so the palm vein pattern is used to authenticate some individual’s identity. The process of authentication and registration is discussed in next topics. An individual first rests his wrist, and on some devices, the middle of his fingers, on the sensor's supports such that the palm is held centimetres above the device's scanner, which flashes a near-infrared ray on the palm [6]. Unlike the skin, through which near-infrared light passes, deoxygenated haemoglobin in the blood flowing through the veins absorbs near-infrared rays, illuminating the haemoglobin, causing it to be visible to the scanner
Arteries and capillaries, whose blood contains oxygenated haemoglobin, which does not absorb near-infrared light, are invisible to the sensor. The still image captured by the camera, which photographs in the near-infrared range, appears as a black network, reflecting the palm's vein pattern against the lighter background of the palm. An individual's palm vein image is converted by algorithms into data points, which is then compressed, encrypted, and stored by the software and registered along with the other details in his profile as a reference for future comparison. Then, each time a person logs in attempting to gain access by a palm scan to a particular bank account or secured entryway, etc., the newly captured image is likewise processed and compared to the registered one or to the bank of stored files for verification, all in a period of seconds.
2.4 PERFORMANCE METRICS OF BIOMETRIC SYSTEM
FALSE ACCEPTANCE RATE (FAR)
The probability that the system incorrectly matches the input pattern to a non-matching template in the database. It measures the percent of invalid inputs which are incorrectly accepted [5].
FALSE REJECTION RATE (FRR)
The probability that the system fails to detect a match between the input pattern and a matching template in the database. It measures the percent of valid inputs which are incorrectly rejected [5].
EQUAL ERROR RATE OR CROSSOVER ERROR RATE (EER OR CER)
The rate at which both accept and reject errors are equal. The value of the EER can be easily obtained from the ROC curve [5]. The EER is a quick way to compare the accuracy of devices with different ROC curves. In general, the device with the lowest EER is most accurate. Obtained from the ROC plot by taking the point where FAR and FRR have the same value. The lower the EER, the more accurate the system is considered to be.
RELATIVE OPERATING CHARACTERISTICS OR RECEIVER OPERATING CHARACTERISTICS (ROC)
The ROC plot is a visual characterization of the trade-off between the FAR and the FRR. In general, the matching algorithm performs a decision based on a threshold which determines how close to a template the input needs to be for it to be considered a match[5]. If the threshold is reduced, there will be less false non-matches but more false accepts. Correspondingly, a higher threshold will reduce the FAR but increase the FRR.
A common variation is the Detection error trade-off (DET), which is obtained using normal deviate scales on both axes. This more linear graph illuminates the differences for
higher performances (rarer errors).
2.5 HOW SECURE IS THE TECHNOLOGY ?
On the basis of testing the technology on more than 70,000 individuals , Fujitsu declared that the new system had a FRR of 0.01% FAR of 0.00008% . Also, if your profile is registered with your right hand, don't log in with your left - the patterns of an individual's two hands differ. And if you registered your profile as a child , it'll still be recognized as you grow, as an individual's patterns of veins are established in uterus (before birth). No two people in the world share a palm vein pattern, even those of identical twins differ. In addition the device ability to perform personal authentication was verified using the following:
1. Data from people ranging from 6 to 85 years old including people in various occupations in accordance with the demographics realized by the Statistics Canter of the Statistics Bureau.
2. Data about foreigners living in Japan in accordance with the world demographics released by the United Nations.
3. Data taken in various situations in daily life including after drinking alcohol, taking bath, going outside and waking up.
2.6 FEATURES OF PALM VEIN TECHNOLOGY
1. The human palm vein pattern is extremely complex and it shows a huge number of vessels.
2. The biometric information is located inside the human body, and therefore it is protected against forgery and manipulation.
3. The position of the palm vein vessels remain the same for the whole life and its
pattern is absolutely unique.
4. The enrolment of the palm vein pattern can be done without any physical contact to the sensor.
5. Skin colour, skin dirtying, surface wounds, skin humidity, skin temperature, aging do not have major influence to enrol and to authenticate the palm vein pattern correctly.
6. Palm Secure is based on a near infrared method, and it has no negative influence to the health.
7. Since it is contact less and uses infrared beam, it is more hygienic.
2.7 WHAT HAPPENS IF THE REGISTERED PALM GETS DAMAGED?
There may be a chance that the palm we had registered may get damaged then we cannot use this technology, so during the time of registration we take the veins of both the hands so that if one gets damaged we can access through the second hand. When hand get damaged up to large extent we can get veins because deeper into the hand veins are obtained.
Chapter-3
PALM VEIN PATTERN EXTRACTION
Palm Vein Technology uses different algorithms and programmes for different stages of the technology [6]. Also different algorithms are proposed for same processes like ICP (Iterative Closest Point), P2PM (Point to Point Matching), SMM (Similarity based Mixed Matching) etc. which we will discuss in next chapter. Usually, in the image-based biometric systems, a number of pre-processing tasks are required prior to enhance the image quality, such as: contrast, brightness, edge information, noise removal, sharpen image, etc, furthermore, to produce a better quality of image that will be used on the later stage as an input image and assuring that relevant information can be detected. Actually, the better quality of image will gain the better accuracy rate to the biometric system itself. In this paper we propose three required pre-processing tasks which are as follow:
1. Vascular pattern marker algorithm
2. Vascular pattern extraction algorithm
3. Vascular pattern thinning algorithm
After vascular pattern thinning, extracted image is matched with the previously stored database, for which various algorithm are used which are to be discussed in next chapter. Here we will discuss the palm vein pattern extraction [6].
3.1 VASCULAR PATTERN MARKER ALGORITHM
1. Open Near-Infrared Palm Image File in input mode.
2. Convert the Loaded Image into Planar Image.
3. Set the Horizontal and Vertical kernels (3 x 3), respectively as follow:
1 0 -1 1 3 1
3 0 -3 0 0 0
1 0 -1 3 x 3 -1 -3 -1 3 x 3
4. Generated Planar Image in Step2, is passed through kernels created in
ABSTRACT
With the increase in technology threat to personal data and national security had also increased. The methods that were developed to secure important information from outside intervention were not up to safe mark .There was a need to introduce a technology that secures our data more efficiently from unlawful intervention .
Fujitsu has developed a palm vein pattern authentication technology that uses vascular patterns as personal identification data .Vein recognition technology is secure because the authentication data exists inside the body and is therefore very difficult to forge. It is highly accurate. This technology can be used in various fields like banking, hospitals, government offices, in passport issuing etc. Business growth will be achieved with these solutions by reducing the size of the palm vein sensor and shortening the authentication time.
Hand vein is a biometric modality that seems promising as it is acquired in Near Infrared light (NIR), which implies that skin variations and dirtiness are less sensible than in visible light. Moreover, the haemoglobin which flows in the veins is sensible to NIR light, this way allowing a good quality of acquisition of the hand veins. It is possible to use either the back of the hand or the hand palm. A recent study using back hand vein data and tested with 5 sessions per person and 50 persons showed promising results. The main problem of this database is the low resolution of the images (images at resolution
132x124 pixels).
The first commercialized products have been produced by Hitachi on the back and Fujitsu on the palm. They have been patented but only little information is available on them. These companies claim a very low FRR ( False Rejection Rate) at very low FAR (False Acceptance Rate) on a huge database – close to 0% on 140000 hands. Unfortunately at this moment, there is no public database allowing verifying these figures. In general, in the various papers present in the literature, after the acquisition phase, some matching
algorithms are used such as the Line segment Hausdorff Distance (LHD) method. The LHD method has good experiment results. But, the structure information of palm vein is not as clear as hand vein, so line-based feature is not a good choice for palm vein recognition. Matching based on minutiae analysis and Hausdorff distance (MHD) was used for hand vein recognition. Minutiae-like feature could also be extracted from palm vein pattern; however, the Hausdorff distance algorithm applied in minutiae analysis is sensitive to the geometrical transformation. Besides P2PM, LHD and MHD, all existing matching methods suffer from the problem of image rotation and shift. Therefore, it is necessary to develop a new matching method which can effectively solve this problem. This paper presents a new and efficient matching method by introducing the iterative closest point (ICP) algorithm into palm vein verification. The ICP algorithm was firstly proposed by Besl and McKay and it was originally used in the registering of three dimensional (3D) range images. It is also well suited to align two dimensional (2D) images. In the proposed method, we first extract vein information from the Region of Interest (ROI). When matching two ROIs, we use ICP to estimate the rotation R and translation T between them. Then we use the estimated R and T to correct the ROIs so as to reduce the rotation and shift variations. The refined alignment of ROIs can bring great benefit in the consequent palm vein verification. The detail of ICP algorithm is explained later in the report. This paper is about the palm vein technology, its applications, how this technology is applied in real time applications and the advantages of using this technology.
Chapter-1
INTRODUCTION TO BIOMETRICS
1.1 WHAT IS BIOMETRICS?
Automated measurement of Physiological and/or behavioral characteristics to determine or authenticate identity is known as Biometrics [5]. Three components of above definition will determine what is and what is not a biometric and also its different types and functionalities.
Let’s start with the First component of the definition: “Automated measurement”, which means no human intervention or involvement is required. Biometrics are automated in as much as the processes involved in sample acquisition, feature extraction, record retrieval, and algorithm-based matching are computerized or machine-based. Also the record retrieval and comparison against another measurement must take place in Real- Time. So for an instance, DNA sampling is NOT a biometric measurement because today it still requires human intervention and it’s NOT done in real time. The second component of the definition: “Physiological and/or behavioral characteristics”, determine the two main biometric categories: behavioral and physiological. The behavioral characteristics measure the movement of a user, when users walk, speak, type on a keyboard or sign their name. The physiological characteristics would be the physical human traits like fingerprints, hand shape, eyes and face, veins, etc., and the last component of the definition is “determine or authenticate identity”, which categorizes the two types of biometric functionalities[5]. The first type is identification systems or the systems that answer the question who am I? and determine the identity of a person. The second type is verification systems or systems that answer the question, am I who I claim to be? and authenticate a person.
An example of an Identification System using biometrics would be: You approach an ATM with NO card, NO claimed identity, NO PIN. The ATM scans your iris and determines who you are and gives you access to your money.
An example of a Verification System using biometrics would be: You approach an ATM and swipe a card or enter an account number. The ATM scans your iris and uses it as a password to authenticate you are the rightful owner of the card and therefore give you access to your money.
1.2 USAGE OF BIOMETRIC TECHNOLOGY MINIMIZES RISKS
The person, who has my office id card, can…
The person, who has my house key, can…
The person, who knows my password, can…
The person, who knows the pin number of my credit card, can…
The person, who is able to forge my signature, can…
The person, who steals my passport, can…
1.4 BIOMETRIC FEATURES
It becomes obsolete to beware passwords safely or to remember to all of them.
Abuse of stolen id cards and passports will be reduced enormously.
Abuse of stolen credit cards will be prevented.
Taking over foreign identities will be impossible.
Building access right to people without the right of admittance will be prevented.
Access to devices/computers will be not possible for persons without the right of admittance.
Unnecessary costs will be drastically reduced.
Level of common convenience and safety will grow.
1.5 DIFFERENT BIOMETRIC TECHNOLOGIES
Voice Print Technology
Finger/palm Print Technology
Face Recognition Technology
Iris Scan Technology
Retina Scan Technology
Ear shape recognition Technology
Dynamic Signature Recognition (DSR)
Typing Pattern Technology
Gait Recognition Technology
Palm Vein Technology
THE BASIS OF PALM VEIN TECHNOLOGY
Every individual have unique pattern of Palm veins, so the palm vein pattern is used to authenticate some individual’s identity. The process of authentication and registration is discussed in next topics. An individual first rests his wrist, and on some devices, the middle of his fingers, on the sensor's supports such that the palm is held centimetres above the device's scanner, which flashes a near-infrared ray on the palm [6]. Unlike the skin, through which near-infrared light passes, deoxygenated haemoglobin in the blood flowing through the veins absorbs near-infrared rays, illuminating the haemoglobin, causing it to be visible to the scanner
Arteries and capillaries, whose blood contains oxygenated haemoglobin, which does not absorb near-infrared light, are invisible to the sensor. The still image captured by the camera, which photographs in the near-infrared range, appears as a black network, reflecting the palm's vein pattern against the lighter background of the palm. An individual's palm vein image is converted by algorithms into data points, which is then compressed, encrypted, and stored by the software and registered along with the other details in his profile as a reference for future comparison. Then, each time a person logs in attempting to gain access by a palm scan to a particular bank account or secured entryway, etc., the newly captured image is likewise processed and compared to the registered one or to the bank of stored files for verification, all in a period of seconds.
2.4 PERFORMANCE METRICS OF BIOMETRIC SYSTEM
FALSE ACCEPTANCE RATE (FAR)
The probability that the system incorrectly matches the input pattern to a non-matching template in the database. It measures the percent of invalid inputs which are incorrectly accepted [5].
FALSE REJECTION RATE (FRR)
The probability that the system fails to detect a match between the input pattern and a matching template in the database. It measures the percent of valid inputs which are incorrectly rejected [5].
EQUAL ERROR RATE OR CROSSOVER ERROR RATE (EER OR CER)
The rate at which both accept and reject errors are equal. The value of the EER can be easily obtained from the ROC curve [5]. The EER is a quick way to compare the accuracy of devices with different ROC curves. In general, the device with the lowest EER is most accurate. Obtained from the ROC plot by taking the point where FAR and FRR have the same value. The lower the EER, the more accurate the system is considered to be.
RELATIVE OPERATING CHARACTERISTICS OR RECEIVER OPERATING CHARACTERISTICS (ROC)
The ROC plot is a visual characterization of the trade-off between the FAR and the FRR. In general, the matching algorithm performs a decision based on a threshold which determines how close to a template the input needs to be for it to be considered a match[5]. If the threshold is reduced, there will be less false non-matches but more false accepts. Correspondingly, a higher threshold will reduce the FAR but increase the FRR.
A common variation is the Detection error trade-off (DET), which is obtained using normal deviate scales on both axes. This more linear graph illuminates the differences for
higher performances (rarer errors).
2.5 HOW SECURE IS THE TECHNOLOGY ?
On the basis of testing the technology on more than 70,000 individuals , Fujitsu declared that the new system had a FRR of 0.01% FAR of 0.00008% . Also, if your profile is registered with your right hand, don't log in with your left - the patterns of an individual's two hands differ. And if you registered your profile as a child , it'll still be recognized as you grow, as an individual's patterns of veins are established in uterus (before birth). No two people in the world share a palm vein pattern, even those of identical twins differ. In addition the device ability to perform personal authentication was verified using the following:
1. Data from people ranging from 6 to 85 years old including people in various occupations in accordance with the demographics realized by the Statistics Canter of the Statistics Bureau.
2. Data about foreigners living in Japan in accordance with the world demographics released by the United Nations.
3. Data taken in various situations in daily life including after drinking alcohol, taking bath, going outside and waking up.
2.6 FEATURES OF PALM VEIN TECHNOLOGY
1. The human palm vein pattern is extremely complex and it shows a huge number of vessels.
2. The biometric information is located inside the human body, and therefore it is protected against forgery and manipulation.
3. The position of the palm vein vessels remain the same for the whole life and its
pattern is absolutely unique.
4. The enrolment of the palm vein pattern can be done without any physical contact to the sensor.
5. Skin colour, skin dirtying, surface wounds, skin humidity, skin temperature, aging do not have major influence to enrol and to authenticate the palm vein pattern correctly.
6. Palm Secure is based on a near infrared method, and it has no negative influence to the health.
7. Since it is contact less and uses infrared beam, it is more hygienic.
2.7 WHAT HAPPENS IF THE REGISTERED PALM GETS DAMAGED?
There may be a chance that the palm we had registered may get damaged then we cannot use this technology, so during the time of registration we take the veins of both the hands so that if one gets damaged we can access through the second hand. When hand get damaged up to large extent we can get veins because deeper into the hand veins are obtained.
Chapter-3
PALM VEIN PATTERN EXTRACTION
Palm Vein Technology uses different algorithms and programmes for different stages of the technology [6]. Also different algorithms are proposed for same processes like ICP (Iterative Closest Point), P2PM (Point to Point Matching), SMM (Similarity based Mixed Matching) etc. which we will discuss in next chapter. Usually, in the image-based biometric systems, a number of pre-processing tasks are required prior to enhance the image quality, such as: contrast, brightness, edge information, noise removal, sharpen image, etc, furthermore, to produce a better quality of image that will be used on the later stage as an input image and assuring that relevant information can be detected. Actually, the better quality of image will gain the better accuracy rate to the biometric system itself. In this paper we propose three required pre-processing tasks which are as follow:
1. Vascular pattern marker algorithm
2. Vascular pattern extraction algorithm
3. Vascular pattern thinning algorithm
After vascular pattern thinning, extracted image is matched with the previously stored database, for which various algorithm are used which are to be discussed in next chapter. Here we will discuss the palm vein pattern extraction [6].
3.1 VASCULAR PATTERN MARKER ALGORITHM
1. Open Near-Infrared Palm Image File in input mode.
2. Convert the Loaded Image into Planar Image.
3. Set the Horizontal and Vertical kernels (3 x 3), respectively as follow:
1 0 -1 1 3 1
3 0 -3 0 0 0
1 0 -1 3 x 3 -1 -3 -1 3 x 3
4. Generated Planar Image in Step2, is passed through kernels created in