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Face Reader
Bučko, Peter ; Juránek, Roman (referee) ; Beran, Vítězslav (advisor)
This thesis deals with computer face recognition. Methods of Components Analysis (PCA), Linear Discriminant Analysis (LDA) and Elastic Bunch Graph Matching (EBGM) are described here. Aim of this thesis is creation of a demonstration aplication for a face recognition. Moreover I test PCA and LDA methods to find out, how accurate it can be and how can be affected by changing of parameters, such as size of a database and picture count per person.
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Accelerating Face Anti-Spoofing Algorithms
Beňuš, Ondřej ; Havel, Jiří (referee) ; Veselý, Karel (advisor)
Tato práce se specializuje na akceleraci algoritmu z oblasti obličejově zaměřených anti-spoofing algoritmů s využitím grafického hardware jakožto platformy pro paralelní zpracování dat. Jako framework je použita technologie OpenCL která umožňuje použití od výkoných stolních počítačů po přenosná zařízení, od různých akcelerátorů jako grafické čipy, či ASIC až po procesory typu x86 bez vazby na konkrétního výrobce či operační systém. Autor předkládá čtenáři rozbor a akcelerovanou implementaci široce používaného algoritmu a dopadu urychlení výpočtu.
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Image processing using Android device
Korchakov, Sergei ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
This master’s Thesis focuses on image processing on Android platform and development of an application, that is able to do face detection and recognition in real scene. Thesis gives highlight of modern algorithms of face detection. It first examines and compares the standard features of Android platform (FaceDetector a FaceDetectionListener) and JJIL, OpenIMAJ, OpenCV libraries experiment, and presents the results. For purposes of face recognition was selected OpenCV library. Three different algorithms of identification were tested: FisherFaces, EigenFaces a Local Binary Patterns Histograms. Based on performance comparison best methods were implemented in developed application.
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Face recognition in video sequences
Malach, Tobiáš ; Průša,, Zdeněk (referee) ; Slanina, Martin (advisor)
This thesis deals with design, implementation and testing of face recognition system processing video sequences captured by CCTV systems. The use of Local Binary Pattern Histograms (LPBH) and Nearest Neighbor (NN) classifier was suggested according to the survey of face recognition methods. Discrimination power of LBPH features was examined and individual informative features were searched based on Fisher discrimination ratio and mutual correlation. Cluster’s centorid method was utilized for pattern creation because of its best effect on system’s face recognition capability comparing several proposed methods. Software tool for effective face recognition system algorithms performance testing was developed. Video database IFaViD was assembled for training and performance testing of implemented face recognition system.
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Face recognition in digital images
Hauser, Václav ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
This master thesis deals with the detection and recognition of faces in the image. The content of this thesis is a description of methods that are used for the face detection and recognition. Method described in detail is the principal component analysis (PCA). This method is subsequently used in the implementation of face recognition in video sequence. In conjunction with the implementation work describes the OpenCV library package, which was used for implementation, specifically the C ++ API. Finally described application tests were done on two different video sequences.
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Video database for face feature recognition
Stříteský, Jan ; Říha, Kamil (referee) ; Vlach, Jan (advisor)
This work compares face databases freely accessible on the Internet which are suitable for the testing of developed algorithms for facial features recognition in a picture. In the course of the work’s project a new face video database was created, encompassing a total of 51 samples. The video database includes a simple application suitable for searching through its contents. In order to limit the size of the video database, compression of individual picture samples was conducted. The created video database can be implemented for testing algorithms for facial features recognition (e.g. face detection in a video, identification of a person, detection of eye blinking, speech recognition).
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Development of algorithms for digital real time image processing on a DSP Processor
Knapo, Peter ; Sajdl, Ondřej (referee) ; Belgium, Jurgen Baert (MSc), KHBO (advisor)
Rozpoznávanie tvárí je komplexný proces, ktorého hlavným ciežom je rozpoznanie žudskej tváre v obrázku alebo vo video sekvencii. Najčastejšími aplikáciami sú sledovacie a identifikačné systémy. Taktiež je rozpoznávanie tvárí dôležité vo výskume počítačového videnia a umelej inteligencií. Systémy rozpoznávania tvárí sú často založené na analýze obrazu alebo na neurónových sieťach. Táto práca sa zaoberá implementáciou algoritmu založeného na takzvaných „Eigenfaces“ tvárach. „Eigenfaces“ tváre sú výsledkom Analýzy hlavných komponent (Principal Component Analysis - PCA), ktorá extrahuje najdôležitejšie tvárové črty z originálneho obrázku. Táto metóda je založená na riešení lineárnej maticovej rovnice, kde zo známej kovariančnej matice sa počítajú takzvané „eigenvalues“ a „eigenvectors“, v preklade vlastné hodnoty a vlastné vektory. Tvár, ktorá má byť rozpoznaná, sa premietne do takzvaného „eigenspace“ (priestor vlastných hodnôt). Vlastné rozpoznanie je na základe porovnania takýchto tvárí s existujúcou databázou tvárí, ktorá je premietnutá do rovnakého „eigenspace“. Pred procesom rozpoznávania tvárí, musí byť tvár lokalizovaná v obrázku a upravená (normalizácia, kompenzácia svetelných podmienok a odstránenie šumu). Existuje mnoho algoritmov na lokalizáciu tváre, ale v tejto práci je použitý algoritmus lokalizácie tváre na základe farby žudskej pokožky, ktorý je rýchly a postačujúci pre túto aplikáciu. Algoritmy rozpoznávania tváre a lokalizácie tváre sú implementované do DSP procesoru Blackfin ADSP-BF561 od Analog Devices.
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Face Detection and Recognition
Ponzer, Martin ; Janáková, Ilona (referee) ; Horák, Karel (advisor)
This paper discusses problems of computer vision, which deals with face detection and recognition in image and video sequence at real time. All methods are designed for color images and are based on skin detection on the basis of information of human skin color. For skin detection is used very effective method Gaussian distribution. All of the areas, which have human skin color, are classified. This classification specifies, which area is or isn’t face. For face detection is used correlation method, complete with eigenfaces method. All areas classified as a face are subsequently recognized by the eigenfaces method. Result of recognition phase is information about human identity.
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The simulation of biometric protection systems working on the face recognition principle
Dubský, Milan ; Rampl, Ivan (referee) ; Atassi, Hicham (advisor)
The aim of this work is to realize a system in the Matlab-Simulink environment, which will be able to detect and recognize the human face from the input image. The created model will actually simulate the biometric security systems working on the principle of face recognition. The work is divided into two parts. In the first part, several methods for face detection from image are described. We focused on the symptomatic oriented and color segmentation methods. The pattern matching method is also described and implemented; the advantage ofthe pattern matching that it can be used either for face detection or face recognition. The second part of this work contains a description of the face recognition. Where PCA (Principal Component Analysis) are used for this task, this part of the work also includes experimental results of tests performed on our methods.
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The use of biometrics in IT
Bílý, Petr ; Balada, Jakub (advisor) ; Šedivá, Zuzana (referee)
Biometrics is increasingly applied in IT (biometric methods today generally use computer technology), mostly used to authenticate users. The aim of this thesis is to describe and compare two selected biometric methods. These methods are fingerprints and scanning of human face. The contribution of this work is to provide information on biometric identification methods, their advantages and disadvantages, and deployment options. If an organization decides to strengthen their security systems with introduction of biometric identification / verification systems, they can find information about these systems, types of sensing devices and their advantages and disadvantages. This work will provide an answer WHY introdukce and use these systems to persons who are responsible for the security policy. The first part after the introduction contains basic concepts in the field of biometric identification, followed by a general overview of the stages of biometric processing (from data collection to their storage), the main areas of use of biometric identification (corporate sphere, security of persons and property, law enforcement agencies and the courts, banking and e-commerce, travel and tourism, and telecommunications), measuring performance in biometrics. Then follow the main chapters of work consisting of two chosen methods of biometric identification (fingerprints and face) and their summaries in the form of mapping advantages and disadvantages.
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