Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disciplines; this reflects its broad appeal and usefulness as one of the steps in exploratory data analysis. However, clustering is a difficult problem combinatorially, and differences in assumptions and contexts in different communities has made the transfer of useful generic concepts and methodologies slow to occur. This paper presents an overview of pattern clustering methods from a statistical pattern recognition perspective, with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering practitioners. We present a taxonomy of clustering techniques, and identify cross-cutting themes and recent advances. We also describe some important applications of clustering algorithms such as image segmentation, object recognition, and information retrieval.

/pdf/data-clustering-a-review-4c452f5cab.pdf

Data clustering: a review

A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators

/pdf/handbook-of-fingerprint-recognition-16mh887j24.pdf

Handbook of Fingerprint Recognition

In order to ensure that the performance of an automatic fingerprint identification/verification system will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement algorithm in the minutiae extraction module. We present a fast fingerprint enhancement algorithm, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency. We have evaluated the performance of the image enhancement algorithm using the goodness index of the extracted minutiae and the accuracy of an online fingerprint verification system. Experimental results show that incorporating the enhancement algorithm improves both the goodness index and the verification accuracy.

/pdf/fingerprint-image-enhancement-algorithm-and-performance-405diava9j.pdf

Fingerprint image enhancement: algorithm and performance evaluation

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

IEEE Transactions on Pattern Analysis and Machine Intelligence

The articles in this special section provide a glimpse of the diverse research challenges in adopting blockchain technology into mainstream applications The four articles focus on the following core issues: scalability, transparency versus privacy, standardization, ecosystem, and integration

/pdf/blockchain-from-technology-to-marketplaces-1f9ba5p7ad.pdf

Blockchain: From Technology to Marketplaces

Multilayer perceptrons (MLPs) are one of the most popular neural network models for solving pattern classification and image classification problems. Because of their ability to learn complex decision boundaries, MLPs are used in many practical computer vision applications involving classification (or supervised segmentation). Once the connection weights in a MLP have been learnt, the network can be used repeatedly for classification of new input patterns. Several special-purpose architectures have been described in the literature for neural networks as they are slow on a conventional uniprocessor. In this paper, we describe mapping of MLPs onto Splash 2-a "custom computing machine". The main features of the proposed mapping are: (i) the number of nodes in a layer is not fixed; (ii) the number of layers in the network is not fixed; (iii) it is based on a set of reprogrammable FPGAs and a programmable crossbar; and (iv) it has a significant speedup over a uniprocessor. The mapping has been used for implementing a 3-layer MLP for page segmentation application with an appreciable speedup of approximately 150 over a SPARCstation 20 for one million pattern vectors with 20 features per pattern.

http://ieeexplore.ieee.org/iel4/4997/13717/00631926.pdf

Multilayer perceptrons on Splash 2

A method, an apparatus and an article of manufacture for generating a cardiovascular measurement for individual identification. The method includes acquiring at least one depiction of cardiac anatomy from an individual, extracting at least one quantified representation of cardiac anatomy from the at least one depiction, defining at least one comparison technique between the at least one quantified representation of cardiac anatomy and at least one additional quantified representation of cardiac anatomy, and identifying the individual based on the at least one defined comparison technique.

Unique Cardiovascular Measurements for Human Identification

Traditional fingerprint acquisition is limited to a single image capture and processing. With the advent of faster capture hardware, faster processors, and advances in video compression standards, newer systems capture and exploit video signals for tasks that are difficult using single images. In this chapter, we propose the use of fingerprint video sequences to investigate dynamic behaviors of fingerprints across multiple frames. In particular, we present a novel approach to detect and estimate distortion occurring in compressed fingerprint video streams. Our approach directly works on MPEG-{1,2} encoded fingerprint video bitstreams to estimate interfield flow without decompression and uses this flow information to investigate temporal characteristics of the behaviors of the fingerprints. The joint temporal and motion analysis leads to a novel technique to detect and characterize distortion reliably. The proposed method has been tested on the NIST-24 database, and the results are very promis ing. We also describe a new concept called the “resultant biometrics”—a new type of biometrics that has both a physiological, physical (e.g., force, torque, linear motion, rotation) component and/or temporal characteristic, added by a subject to an existing biometrics. This resultant biometric is both desirable and efficient in terms of easy modification of compromised biometrics and is harder to produce with spoof body parts.

Dynamic Behavior in Fingerprint Videos

An example operation may include one or more of joining, by a host device, a blockchain managed by one or more devices on a decentralized network, the blockchain is configured to use one or more smart contracts that specify transactions among a plurality of end-users, creating on the blockchain the smart contract defining authentication parameters for an authentication of an end-user from the plurality of the end-users, executing the smart contract to perform the authentication of the end-user associated with a transaction based on the authentication parameters by generating an authentication challenge for the transaction, and recording an authentication log produced by the authentication challenge into a metadata of a transaction payload for analytics.

Nalini K. Ratha

Papers

Blockchain: From Technology to Marketplaces

Multilayer perceptrons on Splash 2

Unique Cardiovascular Measurements for Human Identification

Dynamic Behavior in Fingerprint Videos

Strengthening non-repudiation of blockchain transactions