Texture-based palmprint retrieval using a layered search scheme for personal identification

2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Palmprint identification using restricted fusion

2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Palm Print Recognition Using Curve let Transform

In the era of Information Technology, openness of the information is a major concern. As the confidentiality and integrity of the information is critically important, it has to be secured from unauthorized access. Traditional security and identification are not sufficient enough; people need to find a new authentic system based on behavioral & physiological characteristics of person which is called as Biometric. Palm print recognition gives several advantages over the other biometrics such as low resolution, low cost, non-intrusiveness and stable structure features. Now a days Palm print based personal verification system is used in many security application due to its ease of acquisition, high user acceptance and reliability. Various approaches which deal with palm recognition are texture approach, line approach and appearance approach. By using texture approach it is possible to obtain texture sample with low resolution and texture is much more stable as compare to line and appearance. This paper is aimed to analyze the performance of palm print recognition systems using Curvelet features and for dimension reduction PCA is used

Palmprint Recognition Using Different Level of Information Fusion

The aim of this paper is to investigate a fusion approach suitable for palmprint recognition. Several number of fusion stageis analyse such as feature, matching and decision level. Fusion at feature level is able to increase discrimination power in the feature space by producing high dimensional fuse feature vector. Fusion at matching score level utilizes the matching output from different classifier to form a single value for decision process. Fusion at decision level on the other hand utilizes minimal information from a different matching process and the integration at this stage is less complex compare to other approach. The analysis shows integration at feature level produce the best recognition rates compare to the other method

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Tohoku University青木孝文課

Biometrics

Biometrics-Unique and Diverse Applications in Nature, Science, and Technology provides a unique sampling of the diverse ways in which biometrics is integrated into our lives and our technology. From time immemorial, we as humans have been intrigued by, perplexed by, and entertained by observing and analyzing ourselves and the natural world around us. Science and technology have evolved to a point where we can empirically record a measure of a biological or behavioral feature and use it for recognizing patterns, trends, and or discrete phenomena, such as individuals' and this is what biometrics is all about. Understanding some of the ways in which we use biometrics and for what specific purposes is what this book is all about

Recent Application in Biometrics

In the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers