ON BIOMETRIC SYSTEMS

Biometric has taken from the Greek word “bios” meaning life, and “Metrikos” managing measurement and has introduced an Environmental Meter. A biometric system is essentially a pattern recognition system which recognizes a person based on special features, specific physiological or behavior vectors. The obtained feature vectors are stored in the database. Generally, a biometric system based on physiological characteristics has a high reliability. In this paper, we try to bring some of biometric identification techniques alongside their advantages and disadvantages. *Department of Computer Engineering, Omidiyeh Branch, Islamic Azad University, Omidiyeh, Iran International Journal of Advanced Research in Engineering and Applied Sciences ISSN: 2278-6252 Vol. 2 | No. 7 | July 2013 www.garph. co.uk IJAREAS | 2 1INTRODUCTION Since beginning, human beings are needed to distinguish friend from foe for survival and identification has been always critical for him; so these days have been tried to mechanization the identification or authentication systems. “These developments have been based on the needs of society and the world” [1]. A need for improvements which in caused to reduce fraud, enhance security and accelerate the routines issues. In the past, in order to identify the crime and the criminal, fingerprints and portraits detecting procedures were used but these days a mechanized system is established to do so. Biometric technology can be divided into two general categories (Figure 1): 1 Physiological biometric techniques 2 Behavioral biometric techniques Figure 1: Variety of methods to help identify the biometric features Behavioral biometric technique has four main sections: 1– Sensor Block: responsible for receiving biometric information 2Extracting Features Block: it takes the taken information to extract its vector features 3Comparing Block: responsible for comparing the gained vector with templates 4Decision Block: this section identifies identity, so either accept or reject identity. Biometrics science is seeking a way to identify people unique features related to the human body. It is expected that this method be better than previous traditional methods. In practical applications, the performance of system is: The balance of giving the wrong diagnosis (FAR) and the percentage of not giving the wrong diagnosis (FRR). A good International Journal of Advanced Research in Engineering and Applied Sciences ISSN: 2278-6252 Vol. 2 | No. 7 | July 2013 www.garph. co.uk IJAREAS | 3 biometric identifier that can be used as biometric features in the system should have the following characteristics: 1Uniqueness: Each person is unique and has the distinctive features with others. 2Extracting accountability: the feature could be gained quickly and without the need for high processing for each individual case. 3High resolution capabilities: the difference between two persons is too different to be easily separable. 4Sustainability: the extracted features remain unchanged over time and due to changes in a person's life. In continue and according to Figure 2, we will be introducing some of the most widely used biometrics. Figure 2: some of the most widely used biometrics 2IDENTIFICATION OF PEOPLE BASED ON THEIR GAIT Numerous methods have been presented to identify the identification of people based on their gait in video images which they can be classified into two general categories: statistical approaches and model-based approaches, the proposed approach consists of three phases: pre-processing, feature extraction, and recognition. Evaluation of this approach shows that usually a simple background removal algorithm is done in the preprocessing phase and no serious work has been done in this phase. In the proposed method to identify people from their gait, the pre-processing is used in order to accurately estimate of the background and International Journal of Advanced Research in Engineering and Applied Sciences ISSN: 2278-6252 Vol. 2 | No. 7 | July 2013 www.garph. co.uk IJAREAS | 4 for object detection of the new approach based on fuzzy sets, and in recognition phase a new algorithm is used based on Warping Dynamic Time. DTW is a method based on dynamic programming technique for non-linear time normalization. In this method, the Euclidean distance of each sequence of feature vectors extracted from the test image is calculated with the each component of the reference sequence of feature vectors [2]. 3FINGERPRINT IDENTIFICATION Fingerprint identification is the oldest and best-known method of biometric identification for individuals. But, however, the fingerprint identification has been subjected to major changes in recent years. In the new methods-instead of stamp and paper special scanners have been used which has the ability to assess and adapt the fingerprint with recorded samples. Each person has a different fingerprint. Fingerprint identification is one of the most common methods of identification; so that even the staff attendance systems and some new laptops have been used this method as a reliable and rapid method. On the other hand, there are some practical problems in fingerprint identification systems. Due to the elasticity of the skin, there may be distortions in the shape and location of the fingerprint. In addition, high reliability and real-time processing are important factors in automatic fingerprint identification. To solve this problem, plug extraction from fingerprint images and its application in fingerprint matching is examined [3]. 3-1Fingerprint analysis methods Not all images are fully maintained to minimize the fingerprint data in a database. First, the entire image is analyzed, and then its key points are stored. This action is very important to a quick search in databases. Each fingerprint image has about 35 important features such as cross points, end points, forks and so on (Figure 3) which so-called “minutiae”. ‫To detect and notify any fingerprints with certainty 8 to 22 features are sufficient. The fingerprint profile is stored either directly on the workstation or on a server or on a smart card. International Journal of Advanced Research in Engineering and Applied Sciences ISSN: 2278-6252 Vol. 2 | No. 7 | July 2013 www.garph. co.uk IJAREAS | 5 Figure 3: features of the finger 3-2Fingerprint Classification Classifications of fingerprint are used in identification systems. The goal is to classify a fingerprint database can be divided into smaller parts as possible. In identification systems, the only part of the database is searched that correspond to the categories in terms of the input fingerprint. In systems that work with low population, a class can be used which fingerprints belonging to a single individual characteristics to determine or verify identity. Setting a classification for fingerprint takes place according to the edges direction around the core as well as the number of the core and delta points. In a few cases, a fingerprint cannot be attributed to a particular class, so in any classification system a class is considered to be “unexpected classification” and such these fingerprints are fall into this category. Fingerprints are divided into five main classifications: 1Arc 2Diagonal arc 3Left ring 4Right ring 5Spiral 3-3Identification using hand geometry A CCD camera is used to record the key points of hand in the identification by hand geometry. In this method, the hand’s images are obtained from top and side direction and then are being processed. During this process, some points and lines are assumed on the image. The points and lines are used to measure the length, width and thickness of each of the fingers. Identification system then stores the data in a database until then it is compared International Journal of Advanced Research in Engineering and Applied Sciences ISSN: 2278-6252 Vol. 2 | No. 7 | July 2013 www.garph. co.uk IJAREAS | 6 with the input data to identify the person. The geometric method is not sensitive to dirty hands and so is a good application for workers. Another advantage of this method is its independence of the police and criminal matters so that makes a lot of people willing to sign up in such systems and therefore is suitable for access control applications. It is claimed that it is not possible to indentify the image of one person’s hand among many people and is limited just to confirm the identity of an individual which leads to inefficiency of search applications. Figure 4: Identified by hand geometry 3-4Vein Pattern In this paper, a new method is presented for identifying individuals based on the image of the vessels. This method is useful for access control systems under network coverage(Fig. 5). Figure 5: The condition of the vessel This study was conducted in two stages: registration and data collection and the approval or recognition. In the registrar phase, N numbers of hand images are collected using nearinfrared imaging for different individuals as core academic subjects. The images are being International Journal of Advanced Research in Engineering and Applied Sciences ISSN: 2278-6252 Vol. 2 | No. 7 | July 2013 www.garph. co.uk IJAREAS | 7 processed in pre-processing, feature extraction, and modeling stages so that the adaptive samples are generated and then the neural network is used for the verification. In the discussed method, the preprocessing consists of Image detection threshold, edge detection, edge removing, skeleton extraction vessel, resolution enhancement using morphological functions. In the feature extraction stage, the required vectors are needed to be prepared after applying the wavelet transform to image and statistical feature extraction for comparison in authentication phase. In fact, this technology has been brought a new experience in identification technology and only by using hand vein (vein Pattern the image is obtained by the CCD camera [5]. 3-5Identification by voice In the identification by voice method, first, it ch