1. Abstract
This paper describes a new technique for authenticating handwritten signatures using offline mode. In this technique, every single pixel that belongs to signature is considered. From the signature, every edge points / end points are extracted. These edge points / end points are connected to form a polygonal closed shape. From the polygonal shape, several values can be computed that can serve as structural features that are form factor, circularity measure, rectangularity measure, minimum enclosing rectangle, area and perimeter. These values combine together to make a verification function that can server to discriminate between genuine and forgery signatures.
2. Introduction
Recognizing a person can be done either on the basis of behavioral or physical characteristics in biometric automated methods. There are many behavioral attributes that can be voice, iris, fingerprints, and face recognition. Due to increase in fraud act from forgeries, the need for developing such secure systems for authorizing the right person has increased and these systems needs to be more sensitive to discriminate between genuine and forge person.
Among the different identification methods, the common method used in our society is to identify a person is through handwritten signature because it is an official/formal way for person identification. They are used in government, for attestation, documents authenticity etc. But with its social acceptance it’s demoralized by the forgery to make false transactions. The need is to minimize the forgery threats, research has been done and is still an interesting field for the researchers to minimize forgery signature acceptance.
Automated verificatio...
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Biometrics-based authentication applications include workstation, network, and domain access, single sign-on, application logon, data protection, remote access to resources, transaction security and Web security (Campbell, 1995). Utilized alone or integrated with other technologies such as smart cards, encryption keys and digital signatures, biometrics are set to pervade nearly all aspects of the economy and our daily lives (Campbell, 1995). Among the features measured are; face, fingerprints, hand geometry, iris, and voice (Campbell, 1995).
...ge flow and pattern types, are prominent enough to align fingerprints directly. Nilsson [26] detected the core point by complex filters applied to the orientation field in multiple resolution scales, and the translation and rotation parameters are simply computed by comparing the coordinates and orientation of the two core points. Jain [27] predefined four types of kernel curves:first is arch, second is left loop ,third is right loop and fourth is whorl, each with several subclasses respectively. These kernel curves were fitted with the image, and then used for alignment. Yager [28] proposed a two stage optimization alignment combined both global and local features. It first aligned two fingerprints by orientation field, curvature maps and ridge frequency maps, and then optimized by minutiae. The alignment using global features is fast but not robust, because the
The term biometrics is commonly known as the field of development of statistical and mathematical methods applicable to data analysis problems in the biological sciences. Though, even more recently it has taken on a whole new definition. Biometrics is an amazing new topic referring to “the emerging field of technology devoted to the identification of individuals using biological traits, based on retinal or iris scanning, fingerprints, or face recognition”. Biometrics has already begun using applications that range from attendance tracking with a time clock to security checkpoints with a large volume of people. The growing field of biometrics has really been put on the map by two things, the technological advances made within the last 20 years, and the growing risk of security and terrorism among people all over the world. In this paper I will focus on: the growing field of biometrics, why it is important to our future, how the United States government has played a role in its development and use, the risks involved, the implications on public privacy, and further recommendations received from all over the science and technology field.
Biometrics is, “the automated use of physiological or behavioral characteristics to determine or verify identity (biometricgroup.com, 2014).”16 The purpose of the paper is to provide information about different forms of Biometrics. With the ever increasing threat of terrorism at home and abroad, biometrics is emerging as a way to increase security across the world. It is important to point out current issues dealing with Biometrics and how they relate to people that may one day have to use them.
Fingerprint scanning has already been implemented into business to effectively enhance security and authentications. When scanning a fingerprint, a scanner has to have a pre-saved image of the authorized finger to compare images in a linked database to allow access. In order to allay privacy concerns, however, fingerprint scanners do not store actual fingerprint images. Instead unique characteristics of the fingerprint are analyzed and stored as an encrypted mathematical representation (Ballard, 2016). Businesses are hoping to safeguard their sensitive data by using this form biometrics as a viable option because of the several benefits and low costs. This is a easy to use system with cheap equipment that generally requires low power consumption. However, the disadvantage is that if the surface of the finger is damaged or contains any marks, the identification becomes increasingly difficult. Fingerprint security systems are already
...hniques such as correlation-based matching, minutiae-based matching, and pattern-based (or image-based) matching uses standard dataset for testing purpose. But Practically due to some physical changes in finger during verification ,system gets failed. Various fingerprint matching techniques do not authenticate wrinkled fingers. Thus error rate gets increased when matching is done between dry and wet-wrinkled fingers .Thus proposed system will extract features which will not change even after wrinkling. The proposed system will use minutiae based matching due to which error rate can be reduced. The Wet and Wrinkled Fingerprint (WWF) dataset is used to check the performance of proposed system. In this dataset there are wrinkled fingers due to wetness also some samples of dry fingers. Thus proposed matching algorithm will improve fingerprint recognition for wet fingers.
Within the article the authors point out the use of biometric and multi-modal authentication techniques, pointing out the strengths and weaknesses of different authentication approaches. The article has substantial background information and study results, not only point out the impact of such methods but also shows how the active authentication can take place to benefit the
Biometrics is described as the use of human physical features to verify identity and has been in use since the beginning of recorded history. Only recently, biometrics has been used in today’s high-tech society for the prevention of identity theft. In this paper, we will be understanding biometrics, exploring the history of biometrics, examples of today’s current technology and where biometrics are expected to go in the future.
It is an advanced and newly emerging method for palmprint recognition. It is useful to solve some intractable problems of the first approach .
[3] Jie Chen, Shiguang Shan, Guoying Zhao ‘a robust descriptor based on webers law’ 2008 ieee
[7] Mohammed Alwakeel , Zyad Shaaban ,”Face Recognition Based on Haar Wavelet Transform and Principal Component Analysis via Levenberg-Marquardt Backpropagation Neural Network” in European Journal of Scientific Research,2010 pp. 25-31
Speech is the common basic way we communication with each other. The development of voice biometrics is one that emerged to allow a user to input their voice into a computer system. It is a growing technology which provides security in computers. A speech recognition system is designed to assist the user to complete what that person wants to say versus having a person transcribe it. The first step in voice recognition is for the user to be trained and produce an actual voice sample. Through this process sounds, words or phrases are converted in electrical signals and then they are turned into a coding process by the system. The goal of voice recognition is to understand the human spoken voice.
The invention of biometrics has revolutionized 21st century cyber security like never before and has become an integral part of modern society. Biometrics recognizes an individual’s physical and behavioral characteristics through fingerprint scanning, handprint scanning, voice recognition, etc. However, the problem with biometrics is often times its reliability can be questionable. This issue comes with plenty of symptoms because it can be unreliable in a variety of ways. Previous attempts in finding solutions fail to recognize the replication of data is possible. By solving this problem, security can be ensured more than it is now. Therefore, the advancement of biometrics can only be beneficial. Action does not have to be taken immediately,
As one of the feature of biometric, signature verification is used to find the authenticity of a person to give the access the most valued and important documents and shelf. Firstly the signature of a person are taken as a reference in database. To generate the database, number of attempts from the same person has been taken, as it would permit minute deviations in signatures that generates due to environmental conditions. Once it is done, then the signatures at other times are every time then verified with the existing database. Because of confidentially of the file/document/transaction giving access is the crucial process that should be monitored with perfection. The same happens with offline signature verification. Computerized process and verification algorithm (thus software) takes fully care of signature under test, generate results that are 100% authentic, and advocates credibility of the concerned person .However, there might raise issue of authenticity even if the same person performs the signature. Or, at times a forge person may duplicate the exact signature. Many research have been done to find the accuracy of result so as to prevent from forgery. Forgery is also divided into different categories depending upon their severity as
Iris recognition is very accurate and distinctive because iris has a complex texture that can produce a substantial amount of information to identify a person. Furthermore, the iris remains almost unchanged from childhood, only minuscule variations are presented. The biometric data is captured using a small and high definition camera that is able to recognize different characteristics of the iris. Moreover, the system can detect the use of contact lens with a fake iris and can realize with the natural movement of the eye if the sample object is a living being. Although initially iris recognition systems were expensive and complex to use, new technology developments have improved these weaknesses.