Klasifikasi Pola Sidik Jari Menggunakan Jaringan Syaraf Tiruan Backpropagation

Penelitian ini membahas tentang klasifikasi sidik jari, yang bertujuan untuk mengklasifikasi sidik jari manusia dalam tiga kelas yaitu: whorl, Arch, dan loop. Tahap yang dilakukan adalah preprocessing, segmentasi, ekstrasi ciri dan klasifikasi. Dalam preprocessing yang dilakukan grayscale, median filter, peregangan kontras, histogram. Segmentasi menggunakan metode otsu thresholding dan ekstrasi ciri menggunakan gray level cooccurence matrix (GLCM). Fitur yang digunakan adalah correlation, contrast, energy, homogeneity, dan entropy. Klasifikasi tersebut menggunakan jaringan syaraf tiruan backpropagation. Hasil penelitian system ini dapat mengklasifikasi sidik jari dengan akurasi 87,5%.Kata kunci: GLCM, backpropagation neural networ

A Translation And Rotation Independent Fingerprint Identification Approach

This thesis describes a new approach for fingerprint identification that will be shift and rotation independent. Detailed descriptions of directional filtering, foreground and background segmentation, feature extraction, and matching based on structural correlation are the main topics of this thesis. The fingerprint identification system consists of image preprocessing, feature extraction, and matching which run on a PC platform. The preprocessing step includes histogram equalization, block-based directional filtering, thinning, and adaptive thresholding to enhance the original images for successful feature extraction. The features extracted will be stored in the database for matching. The matching algorithm presented is a modification and improvement of the structural approach. A two-step process of local feature matching and global feature matching guarantees the correct matching results

Embedded Biometric Sensor Devices: Design and Implementation on Field Programmable Gate Array

During the research activity in my Ph.D. course, I thoroughly studied the biometric systems and the relevant design and implementation techniques allowing the employment of such systems in embedded devices. I focused my attention on the fingerprint-based recognition and classification systems, and on their implementation on Field Programmable Gate Array (FPGA) devices. I was prompted to study biometric systems mainly because these systems may play a key role in the new emerging market of mobile devices (for example, they are recently available in the new generation of Apple and Samsung smart phones). Such market is rapidly growing and influencing the way people use network resources and functionalities (such as commercial, banking, and government services), requiring a security level higher than in the past. Consequently, novel design techniques and technologies for user recognition and are required to be investigated, in order to provide a secure services and resources access. The traditional authentication systems based on username and password are not able to guarantee a suitable protection level. Unlike password, instead, user biometric information is unique and unchangeable; therefore the biometric identity has the advantage to guarantee that only the authorized users have access to available resources and services. However, traditional biometric approaches involves interactions among a large number of entities: passive access points for user biometric trait acquisition, networked databases for user biometric identity storing, and trusted servers running the user recognition systems. So, traditional systems usually undergo several types of attacks, such as Communication Attack (attacking the channel between the server and the database), Replay Attack (replication of user biometric trait processed during the acquisition phase), and Database Attack (manipulation of the stored user biometric identity). Embedded architectures, instead, provide a more secure and flexible infrastructure, since all elaboration steps are performed on board, so biometric identities are securely managed and stored inside the system without any data leaking out. The goal of this thesis is to illustrate the analysis and results of my research activity focused on the design and development of new fingerprint-based recognition systems for embedded devices. The study of the state-of-the-art about biometric systems led me to realize novel approaches to improve the performance of standard systems in order to enable their employment in embedded devices architectures. Most common literature approaches used to implement fingerprint-based recognition and classification systems are reported to provide a starting-point for understanding the contribution of this work. There are many literature approaches to deal with software systems, but few on design and implementation of embedded hardware prototypes. Referring to the developed and proposed fingerprint-based systems, this thesis represents an advancement of embedded biometrics respect to state-of-the-art. The step-over proposed in this work is focused on: 1. a heuristic fingerprint classification technique, requiring only a little set of images as training dataset; 2. an advanced matching technique for personal recognition based on partial fingerprint, able to enhance the system accuracy; 3. the design and implementation of an efficient fingerprint features extractor; 4. the design and implementation of a quality evaluator of raw fingerprint images (able to identify poor quality areas, such as dry and moist portions), allowing to define a novel flow of image processing steps for user recognition. This thesis is divided into two parts, creating a path connecting the state-of-the-art about biometric systems and the novel implemented approaches. The knowledge of the state-of-the-art about biometrics is fundamental to understand the step over presented in this work. For this reason, in the first part, general characteristics of biometric systems are presented with particular reference to fingerprint-based approaches used in literature to realize embedded systems. The second part proposes the developed innovative sensor. A novel flow of image processing steps for user recognition is outlined. Successively, an efficient micro and macro fingerprint features extractor is illustrated. Then, an advanced matching technique for personal recognition using partial fingerprints is presented. Finally, an innovative fingerprint classification approach based on the fusion of Fuzzy C-Means and Naive-Bayes technique is detailed. Experimental results and comparisons with analogous literature systems show the effectiveness on the proposed sensor. All the innovative approaches proposed in this thesis have been published in international conferences and journals

Reconhecimento automático de impressões digitais utilizando wavelets e redes neuronais artificiais

This work proposes a new approach for automatic fingerprint recognition. Differently from traditional techniques, based on the analysis of peculiarities existing in fingerprint patterns and dedicated search algorithms for that purpose, it is suggested a methodology centred in signal representation tools and connectionist classification models. Basically, the methodology proposed here supports itself in two main techniques: the FBI’s Wavelet Scalar Quantization standard for fingerprint image compression as method for the feature extraction; and Artificial Neural Networks models that use linear training techniques as method for the classification of the resulting patterns. The main objective of the suggested method is the development of a recognition system independent from specific fingerprint image analysis techniques, looking for low false acceptance and false rejection rates, with priority for the false acceptance rate. The methodologies and results achieved in the executed experiments are presented, as well as their respective analysis and yet some proposals for future work and enhancements. Some aspects pertinent to the image acquisition hardware and some digital image processing techniques are also presented.CNPq, CAPESEste trabalho propõe uma nova abordagem para o reconhecimento automático de impressões digitais. Diferentemente das técnicas tradicionais, baseadas na análise de peculiaridades relativas aos padrões de impressão digital e em algoritmos de busca dedicados especialmente a esse fim, é sugerida uma metodologia com base em ferramentas de representação de sinais e em modelos de classificação conexionistas. Basicamente, a metodologia aqui proposta fundamenta-se em duas técnicas principais: o padrão de compressão wavelet para impressões digitais especificado pelo FBI como método de extração de características; e modelos de Redes Neuronais Artificiais que utilizam técnicas lineares de treinamento como método de classificação dos padrões obtidos. O principal objetivo do método sugerido é o desenvolvimento de um sistema de reconhecimento independente de técnicas específicas de análise e processamento de imagens de impressões digitais, procurando-se a obtenção de baixos índices de falsa aceitação e rejeição, sendo a prioridade para o índice de falsa aceitação. As metodologias e resultados obtidos nos experimentos executados são apresentados, bem como suas respectivas análises e ainda algumas propostas para trabalhos futuros e melhorias. Alguns aspectos pertinentes ao hardware de aquisição de imagens e algumas técnicas de processamento digital de imagens também são apresentadas

Biblioteca para criação de jogos utilizando geração pseudo-randômica paramétrica, realidade-virtual, inteligência artificial e redes de computadores

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Produção.Atualmente os jogos digitais (videogames) envolvem uma fatia considerável de mercado, sendo um negócio de bilhões de dólares (BUSHNELL apud RADINSKY, 1997 www.sjmercury.com/revolutionaries/bushnell.htm, junho 2001). Navegando a rede mundial de computadores, pode-se observar a enorme quantidade de jogos disponíveis, para demonstração e potencial compra pelos usuários cibernéticos. Tais demonstrações são tanto para computadores pessoais como emuladores de sistemas proprietários de videogames. A demanda crescente, junto com o avanço da tecnologia e a concorrência por uma fatia deste mercado, forçam os produtores de jogos a fornecerem produtos e serviços inovadores aos seus clientes, que poderão interagir cada vez mais profundamente com os ambientes virtuais dos jogos digitais, e também com outros clientes, espalhados ao redor do mundo. Sistemas de jogos e periféricos que permitem a interação mais natural com o ser humano, que dão a possibilidade de o usuário interagir com os personagens virtuais através da fala e gestos do corpo, e deixam interagir com outros usuários em outros locais do planeta, ou ainda jogos que são capazes de simular situações e comportamentos parecidos com os personagens da vida real, e produzam ambientes tão imprevisíveis quanto a própria natureza, fazem com que o usuário cada vez mais se convença de que está imerso neste novo mundo virtual. O trabalho a seguir apresenta uma pesquisa feita sobre jogos de computadores, cujo resultado final foi a criação de uma biblioteca de funções para criação de jogos digitais. Tal biblioteca é capaz de conduzir a máquina na geração, através de número randômicos, de mundos imprevisíveis e situações de clima, assim como são no mundo real. A biblioteca criada é capaz de permitir a interação de um usuário com a máquina através de várias interfaces, fazendo com que a comunicação entre usuário e computador seja mais humana. Ela ainda possibilita a interação Finalmente, esta biblioteca possui algoritmos que gerenciam o comportamento de agentes inteligentes, para que também interajam entre si e com os vários usuários do sistema