A Palmprint-Based Identification System using Radon Transform

Biometrics-based personal identification is a powerful security features in the technology era. Palm print is a reliable biometric that can be used for identity verification because it is stable and unique for every individual. The palm print acquired from a charge coupled device (CCD) based camera is preprocessed and the edge of the image is obtained. The palm prints are matched using the AND function and the verification process is based on whether a person is who he/she claims to be. Five hundred verifications were obtained and analyzed. The false acceptance rate (FAR) and false reject rate (FRR) values against different threshold values were plotted and the equal error rate (EER) was acquired. The system's EER is approximately 15% with the verification threshold of 23. Overall, the system has an accuracy of 87.4%.

Pattern Recognition, 2008

In this paper, we propose a novel robust line orientation code for palmprint verification, whose performance is improved by using three strategies. Firstly, a modified finite Radon transform (MFRAT) is proposed, which can extract the orientation feature of palmprint more accurately and solve the problem of sub-sampling better. Secondly, we construct an enlarged training set to solve the problem of large rotations caused by imperfect preprocessing. Finally, a matching algorithm based on pixel-to-area comparison has been designed, which has better fault tolerant ability. The experimental results of verification on Hong Kong Polytechnic University Palmprint Database show that the proposed approach has higher recognition rate and faster processing speed. ᭧

2017

Biometrics is defined as the exceptional or individual physical properties or attributes of human body. These attributes are used to recognize each human. Any details of the person body which differs from another person to the other is used as unique biometrics data which serve to that’s person’s unique ID. Palmprint recognition being one of the important aspects of biometric technology. These palmprint recognition serves into four stages, palmprint image acquisition, preprocessing, feature extraction and matching. The major approach for palmprint recognition is to extract feature vector from each individual palm and to perform matching based on some distance metrics. This paper present a detailed review on palmprint recognition approaches.

2009

Palmprint recognition has been investigated over 10 years. During this period, many different problems related to palmprint recognition have been addressed. This paper provides an overview of current palmprint research, describing in particular capture devices, preprocessing, verification algorithms, palmprintrelated fusion, algorithms especially designed for real-time palmprint identification in large databases and measures for protecting palmprint systems and users' privacy. Finally, some suggestion is offered.

Online palmprint recognition and latent palmprint identification are two branches of palmprint studies. The former uses middle-resolution images collected by a digital camera in a well-controlled or contact-based environment with user cooperation for commercial applications and the latter uses highresolution latent palmprints collected in crime scenes for forensic investigation. However, these two branches do not cover some palmprint images which have the potential for forensic investigation. Due to the prevalence of smartphone and consumer camera, more evidence is in the form of digital images taken in uncontrolled and uncooperative environment, e.g., child pornographic images and terrorist images, where the criminals commonly hide or cover their face. However, their palms can be observable. Among various biometrics technologies, palm-print identification has received much attention because of its good performance. Combining the left and right palm-print images to perform multi-biometrics is easy to implement and can obtain better results. Existing systems deployed Line Based Method, Coding Based Method, Subspace Based Methods, Representation Based Method, SIFT Based Method. This work integrated three kinds of scores generated from the left and right palm-print images to perform matching score-level fusion. The first two kinds of scores were, respectively, generated from the left and right palm-print images and can be obtained by any palm-print identification method, whereas the third kind of score was obtained using a specialized algorithm proposed in this paper. As the proposed algorithm carefully takes the nature of the left and right palm-print images into account, it can properly exploit the similarity of the left and right palm-prints of the same subject. Moreover, the proposed weighted fusion scheme allowed perfect identification performance to be obtained in comparison with previous palm-print identification methods.

International Journal of Computer Applications, 2017

In this paper, an effective biometrics method based on hand geometry is presented for biometric identification or verification system. Biometrics-based authentication is a verification approach using the biological features inherent in each individual. They are processed based on the identical, portable, and arduous duplicate characteristics. The principal lines and texture are two kinds of salient features of palmprint. A few years ago , a new branch of biometrics technology, palmprint authentication was proposed whereby line and points are extracted from palms for personal identification. In this paper, we consider palmprint as a piece of lines and texture and apply palmprint identification techniques for extracting feature to palmprint authentication.

Advances in Computational Intelligence and Robotics

The automatic use of physiological or behavioral characteristics to determine or verify identity of individual's is regarded as biometrics. Fingerprints, Iris, Voice, Face, and palmprints are considered as physiological biometrics whereas voice and signature are behavioral biometrics. Palmprint recognition is one of the popular methods which have been investigated over last fifteen years. Palmprint have very large internal surface and contain several unique stable characteristic features used to identify individuals. Several palmprint recognition methods have been extensively studied. This chapter is an attempt to review current palmprint research, describing image acquisition, preprocessing palmprint feature extraction and matching, palmprint related fusion and techniques used for real time palmprint identification in large databases. Various palmprint recognition methods are compared.

Image processing is widely used in many applications like medical imaging, industrial manufacturing, entertainment and security system. The size of image is very large. Biometrics which use of human physiological characteristics for identifying an individual, now a widespread method of identification and authentication, uses several image processing techniques. Biometric computing offers an effective approach to identify personal identity by using individual's unique, reliable and stable behavioural characteristics. Biometric identification is a technology which describes the general procedure for identification and verification using feature extraction, storage and matching from the digitized image of biometric characters such as Finger Print, Face, Iris or Palm Print. In this paper we present a comparative study and analysis of some palm print feature extraction and identification methods.

2012

A biometric system is essentially a pattern recognition system which makes a personal identification by determining the authenticity of a specific physiological or behavioral characteristic possessed by the user. Biometric has gained much attention in the security world recently. Many types of personal identification systems have been developed and palmprint verification is one of the emerging technologies because of its stable, unique characteristics, low-price capture device, fast execution speed also it provides a large area for feature extraction. Palmprint recognizes a person based on the principal lines, wrinkles and ridges on the surface of the palm. The recognition process consists of image acquisition, preprocessing, feature extraction, matching and result. The different techniques are used for the preprocessing, feature extraction, classifiers. The methods discussed are for the online palmprint recognition.

2014

Palmprint is widely used in personal identification and authentication for a precise and robust recognition. Palmprint recognition has been reconnoitered over numerous years. During this instance of time, several different glitches related to palmprint recognition have been addressed. Furthermost of the studies has been done in palmprint recognition due to its stability, reliability and exclusivity. Furthermore it has been used for law enforcement, civil applications and access control applications. Researchers have proposed a variety of palmprint preprocessing, feature extraction and matching approaches. This paper deliberates about the number of investigation works introduced to overcome the difficulties confronted in each stage of palm print verification. Our study on palm print recognition focuses on verifying the palm print in different types of schemes involved.