Handbook of Fingerprint Recognition (Springer Professional Computing)

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Buy with confidence, excellent customer service!. Seller Inventory q. Never used!. Published by Springer-Verlag, New York Another problem for the early twenty-first century is that during crime scene investigations, a decision has to be made at an early stage whether to attempt to retrieve fingerprints through the use of developers or whether to swab surfaces in an attempt to salvage material for DNA profiling. The two processes are mutually incompatible, as fingerprint developers destroy material that could potentially be used for DNA analysis, and swabbing is likely to make fingerprint identification impossible.

The application of the new scanning Kelvin probe SKP fingerprinting technique, which makes no physical contact with the fingerprint and does not require the use of developers, has the potential to allow fingerprints to be recorded whilst still leaving intact material that could subsequently be subjected to DNA analysis. A forensically usable prototype was under development at Swansea University during , in research that was generating significant interest from the British Home Office and a number of different police forces across the UK, as well as internationally.

The hope is that this instrument could eventually be manufactured in sufficiently large numbers to be widely used by forensic teams worldwide. The secretions, skin oils and dead cells in a human fingerprint contain residues of various chemicals and their metabolites present in the body. These can be detected and used for forensic purposes. For example, the fingerprints of tobacco smokers contain traces of cotinine , a nicotine metabolite; they also contain traces of nicotine itself. Caution should be used, as its presence may be caused by mere contact of the finger with a tobacco product.

By treating the fingerprint with gold nanoparticles with attached cotinine antibodies , and then subsequently with a fluorescent agent attached to cotinine antibodies, the fingerprint of a smoker becomes fluorescent; non-smokers' fingerprints stay dark. Most American law enforcement agencies use Wavelet Scalar Quantization WSQ , a wavelet -based system for efficient storage of compressed fingerprint images at pixels per inch ppi. Fingerprints collected at a crime scene, or on items of evidence from a crime, have been used in forensic science to identify suspects, victims and other persons who touched a surface.

Fingerprint identification emerged as an important system within police agencies in the late 19th century, when it replaced anthropometric measurements as a more reliable method for identifying persons having a prior record, often under a false name, in a criminal record repository. Fingerprints are the fundamental tool in every police agency for the identification of people with a criminal history.

The validity of forensic fingerprint evidence has been challenged by academics, judges and the media. In the United States fingerprint examiners have not developed uniform standards for the identification of an individual based on matching fingerprints. In some countries where fingerprints are also used in criminal investigations, fingerprint examiners are required to match a number of identification points before a match is accepted.

In England 16 identification points are required and in France 12, to match two fingerprints and identify an individual. Point-counting methods have been challenged by some fingerprint examiners because they focus solely on the location of particular characteristics in fingerprints that are to be matched. Fingerprint examiners may also uphold the one dissimilarity doctrine , which holds that if there is one dissimilarity between two fingerprints, the fingerprints are not from the same finger.

Furthermore academics have argued that the error rate in matching fingerprints has not been adequately studied. And it has been argued that fingerprint evidence has no secure statistical foundation.

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Fingerprinting was the basis upon which the first forensic professional organization was formed, the International Association for Identification IAI , in Fingerprints have been found on ancient Babylonian clay tablets, seals, and pottery. In about BC fingerprints were used to sign written contracts in Babylon. In Ancient India some texts called Naadi were written by a Rishi called Agastya where the text is said to predict the past, present, and future lives of all humans from just their thumb prints.

The predictions are based on Naadi palm leaves, which are located in thumb impressions right for men, left for women. With the advent of silk and paper in China, parties to a legal contract impressed their handprints on the document. Although ancient peoples probably did not realize that fingerprints could uniquely identify individuals, [36] references from the age of the Babylonian king Hammurabi reigned — BCE indicate that law officials would take the fingerprints of people who had been arrested.

From the late 16th century onwards European academics attempted to include fingerprints in scientific studies. But plausible conclusions could only be established from the mid 17th century onwards. In the professor of anatomy at the University of Bologna Marcello Malpighi identified ridges, spirals and loops in fingerprints left on surfaces.

In a German anatomist Johann Christoph Andreas Mayer was the first European to recognize that fingerprints were unique to each individual. The nine patterns include the tented arch, the loop, and the whorl, which in modern day forensics are considered ridge details. In he first instituted the use of fingerprints on contracts and deeds to prevent the repudiation of signatures in Hooghly near Kolkata [45] and he registered government pensioners' fingerprints to prevent the collection of money by relatives after a pensioner's death.

In Henry Faulds , a Scottish surgeon in a Tokyo hospital, published his first paper on the usefulness of fingerprints for identification and proposed a method to record them with printing ink. He had calculated that the chance of a "false positive" two different individuals having the same fingerprints was about 1 in 64 billion. In that same year, Francisca Rojas was found in a house with neck injuries, whilst her two sons were found dead with their throats cut.

Rojas accused a neighbour, but despite brutal interrogation, this neighbour would not confess to the crimes. Inspector Alvarez, a colleague of Vucetich, went to the scene and found a bloody thumb mark on a door. When it was compared with Rojas' prints, it was found to be identical with her right thumb. She then confessed to the murder of her sons. In Kolkata a fingerprint Bureau was established in , after the Council of the Governor General approved a committee report that fingerprints should be used for the classification of criminal records.

The bureau employees Azizul Haque and Hem Chandra Bose have been credited with the primary development of a fingerprint classification system eventually named after their supervisor, Sir Edward Richard Henry. The French scientist Paul-Jean Coulier developed a method to transfer latent fingerprints on surfaces to paper using iodine fuming. It allowed the London Scotland Yard to start fingerprinting individuals and identify criminals using fingerprints in Soon after, American police departments adopted the same method and fingerprint identification became a standard practice in the United States.

Alphonse Bertillon identified the thief and murderer Scheffer, who had previously been arrested and his fingerprints filed some months before, from the fingerprints found on a fractured glass showcase, after a theft in a dentist's apartment where the dentist's employee was found dead. It was able to be proved in court that the fingerprints had been made after the showcase was broken.

The identification of individuals through fingerprints for law enforcement has been considered essential in the United States since the beginning of the 20th century. Body identification using fingerprints has also been valuable in the aftermath of natural disasters and anthropogenic hazards. US Visit currently holds a repository of the fingerprints of over 50 million non-US citizens, primarily in the form of two-finger records.

In Edmond Locard established the first forensic lab in France. However, the gloves themselves can leave prints that are as unique as human fingerprints. After collecting glove prints , law enforcement can match them to gloves that they have collected as evidence or to prints collected at other crime scenes. The non-governmental organization NGO Privacy International in made the cautionary announcement that tens of thousands of UK school children were being fingerprinted by schools, often without the knowledge or consent of their parents.

Parents opposed to fingerprinting may only bring individual complaints against schools. In March , the UK government was considering fingerprinting all children aged 11 to 15 and adding the prints to a government database as part of a new passport and ID card scheme and disallowing opposition for privacy concerns. All fingerprints taken would be cross-checked against prints from , unsolved crimes. Shadow Home secretary David Davis called the plan "sinister".

The Liberal Democrat home affairs spokesman Nick Clegg criticised "the determination to build a surveillance state behind the backs of the British people". Lord Adonis reassured the House of Lords that the children's fingerprints had been taken with the consent of the parents and would be destroyed once children left the school. Serious concerns about the security implications of using conventional biometric templates in schools have been raised by a number of leading IT security experts, [63] one of whom has voiced the opinion that "it is absolutely premature to begin using 'conventional biometrics' in schools".

One education specialist wrote in "I have not been able to find a single piece of published research which suggests that the use of biometrics in schools promotes healthy eating or improves reading skills amongst children There is absolutely no evidence for such claims". Since electronic fingerprint readers have been introduced as consumer electronics security applications. Fingerprint sensors could be used for login authentication and the identification of computer users.

However, some less sophisticated sensors have been discovered to be vulnerable to quite simple methods of deception, such as fake fingerprints cast in gels. In , fingerprint sensors gained popularity in the laptop market. Two of the first smartphone manufacturers to integrate fingerprint recognition into their phones were Motorola with the Atrix 4G in and Apple with the iPhone 5S on September 10, In April , Samsung released the Galaxy S5 , which integrated a fingerprint sensor on the home button.

Following the release of the iPhone 5S model, a group of German hackers announced on September 21, , that they had bypassed Apple's new Touch ID fingerprint sensor by photographing a fingerprint from a glass surface and using that captured image as verification.

Handbook of Fingerprint Recognition

The spokesman for the group stated: "We hope that this finally puts to rest the illusions people have about fingerprint biometrics. It is plain stupid to use something that you can't change and that you leave everywhere every day as a security token. The use of the Touch ID fingerprint scanner was optional and could be configured to unlock the screen or pay for mobile apps purchases. It has been alleged that taking the fingerprints of welfare recipients as identification serves as a social stigma that evokes cultural images associated with the processing of criminals.

A very rare medical condition, adermatoglyphia , is characterized by the absence of fingerprints.


Affected persons have completely smooth fingertips, palms, toes and soles, but no other medical signs or symptoms. People with Naegeli—Franceschetti—Jadassohn syndrome and dermatopathia pigmentosa reticularis , which are both forms of ectodermal dysplasia , also have no fingerprints. Both of these rare genetic syndromes produce other signs and symptoms as well, such as thin, brittle hair. The anti-cancer medication capecitabine may cause the loss of fingerprints.

Since the elasticity of skin decreases with age, many senior citizens have fingerprints that are difficult to capture. The ridges get thicker; the height between the top of the ridge and the bottom of the furrow gets narrow, so there is less prominence. Fingerprints can be erased permanently and this can potentially be used by criminals to reduce their chance of conviction. Erasure can be achieved in a variety of ways including simply burning the fingertips, using acids and advanced techniques such as plastic surgery. Fingerprints can be captured as graphical ridge and valley patterns. Because of their uniqueness and permanence, fingerprints emerged as the most widely used biometric identifier in the s.

Automated fingerprint verification systems were developed to meet the needs of law enforcement and their use became more widespread in civilian applications. Despite being deployed more widely, reliable automated fingerprint verification remained a challenge and was extensively researched in the context of pattern recognition and image processing.

Synaptics shows how easy it is to spoof fingerprint recognition

The uniqueness of a fingerprint can be established by the overall pattern of ridges and valleys, or the logical ridge dicontinuities known as minutiae. In the s minutiae features were considered the most discriminating and reliable feature of a fingerprint. Therefore the recognition of minutiae features became the most common basis for automated fingerprint verification. The most widely used minutiae features used for automated fingerprint verification were the ridge ending and the ridge bifurcation.

Scientists have found that family members often share the same general fingerprint patterns, leading to the belief that these patterns are inherited. Features of fingerprint ridges, called minutiae , include: [88]. A fingerprint sensor is an electronic device used to capture a digital image of the fingerprint pattern. The captured image is called a live scan.

This live scan is digitally processed to create a biometric template a collection of extracted features which is stored and used for matching. Many technologies have been used including optical , capacitive , RF , thermal, piezoresistive , ultrasonic , piezoelectric , MEMS.

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Videos have become a pronounced way of identifying information. There are features in videos that look at how intense certain parts of a frame are compared to others which help with identification. Matching algorithms are used to compare previously stored templates of fingerprints against candidate fingerprints for authentication purposes.

In order to do this either the original image must be directly compared with the candidate image or certain features must be compared. Pre-processing helped enhancing the quality of an image by filtering and removing unnecessary noises. The minutiae based algorithm only worked effectively in 8-bit gray scale fingerprint image. A reason was that an 8-bit gray fingerprint image was a fundamental base to convert the image to 1-bit image with value 0 for ridges and value 1 for furrows. As a result, the ridges were highlighted with black color while the furrows were highlighted with white color.

This process partly removed some noises in an image and helped enhance the edge detection. Furthermore, there are two more steps to improve the best quality for the input image: minutiae extraction and false minutiae removal. The minutiae extraction was carried out by applying ridge thinning algorithm which was to remove redundant pixels of ridges.

As a result, the thinned ridges of the fingerprint image are marked with a unique ID so that further operation can be conducted. After the minutiae extraction step, the false minutiae removal was also necessary. The lack of the amount of ink and the cross link among the ridges could cause false minutiae that led to inaccuracy in fingerprint recognition process. Pattern based algorithms compare the basic fingerprint patterns arch, whorl, and loop between a previously stored template and a candidate fingerprint.

This requires that the images can be aligned in the same orientation. To do this, the algorithm finds a central point in the fingerprint image and centers on that. In a pattern-based algorithm, the template contains the type, size, and orientation of patterns within the aligned fingerprint image. The candidate fingerprint image is graphically compared with the template to determine the degree to which they match.

Some other animals have evolved their own unique prints, especially those whose lifestyle involves climbing or grasping wet objects; these include many primates , such as gorillas and chimpanzees, Australian koalas , and aquatic mammal species such as the North American fisher. We obtained these samples by conducting an experiment in an ambient intelligence workplace environment—see Figure 1 —where the participants were asked to act normally, as they would have done in their usual workplace. We began the experiment by analyzing the walking patterns of the users as they headed to their office in non-predefined paths.

Then, extending the theory of Rosenbaum et al.

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We recorded these activities using two depth cameras that capture images at a rate of 30 frames per second. From the captured images we extracted the depth-enhanced gait silhouettes and apply several 1D transformations on them, such as Radon integral or Krawtchouk moments transforms. Both of these manipulations can form efficient descriptors of grayscale images to give compact representations of the original image. To verify the tracking accuracy of the proposed tracker, we simultaneously tracked the movements of the head and all the joints of the arm i. By processing the spatiotemporal activity-related trajectories, we could then extract several features, including the speed, acceleration, jerk, and curvature of the movement.

However, not all of these features have a high discrimination capacity. We evaluated the distinctiveness of the features according their relative entropy and mutual information see Figure 4. We identified that the features with the highest value for incorporation into our system were the trajectories of the head and palm, the velocity of the hand, and the total spatial cost and torsion of the palm.

Although the trajectories of the elbow and the shoulder are of equally high distinctiveness, they can be omitted because they are highly correlated with the trajectories of the palm the end effector. With these features identified, we evaluated the system based on the estimation of the equal error rates EERs among the subjects in the ACTIBIO dataset, 5, 6 which includes data from 29 subjects performing a series of workplace-related activities in different time sessions.

We calculated the EER for different classifiers see Tables 1 and 2 at the optimal performance point as defined by a set of weighting factors for the extracted features, which follows from the findings shown in Figure 4. The first experiment involved the analysis of a short phone activity: someone picking up the telephone, taking it to his or her ear, and then placing it back on the base. This classifier is calculated by measuring the Euclidean distance between points on two trajectories and similarly for other features such as velocity and summing up all the distances the sum is known as the L 1 norm.

We used these two algorithms as classifiers that provide a matching score between the gallery subject-specific signature and the incoming probe vectors. Behavioral biometric modalities are therefore far from forming stand-alone recognition systems. However, their added value can be easily exploited in multimodal architectures. In this respect, we combined gait recognition 3 with behavioral traits from another prehension activity: a user interacting with a person identification number PIN -protected electronic locker panel.

In summary, we have presented a novel system for unobtrusive human recognition from simple activities that are performed regularly on daily basis.

A possible real-world application of such a system would be its integration to high-security controlled areas and infrastructures, such as nuclear plants or classified military areas, where only a small number of users are authorized to have access. We have used invariant and partially view-invariant activity-related traits that are exclusively extracted from camera sensors with depth estimation capabilities. Our system achieves very promising results that favorably outperform state-of-the-art unimodal recognition systems in both performance and level of obtrusiveness.

However, it should be noted that being still in their infancy, these behavioral biometric systems can only be used in an augmentative manner in conventional security solutions. Our future work includes the efficient incorporation of soft biometric traits within an effective recognition framework to achieve further improvements in recognition performance.

For example, height and stride in the gait experiment could be used for recognition purposes in high-security facilities such as nuclear factories and to augment existing recognition methods such as PINs and identification cards. Dimitrios Tzovaras is a senior researcher whose main research interests include visual analytics, 3D object recognition, search and retrieval, behavioral biometrics, assistive technologies, multimodal interfaces, computer graphics, and virtual reality.

Anastasios Drosou holds an MEng in electrical and computer engineering and an MSc in communication engineering. Sign In View Cart 0 Help. News Menu.