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Application for Recognition of Human Eye Retina
Drozd, Radek ; Hájek, Josef (referee) ; Drahanský, Martin (advisor)
The blood vessels layout in a human eye retina is unique for every person in the world, so it is one of important biometric characteristics. Processing of colour retina image may be a part of an intended biometric system. There is an algorithm for automatic blood vessels detection, optic disc and macula localisation, finding of bifurcation points and saving those as a biometric template presented in this bachelor's thesis. C++ programming language and OpenCV library were used for implementation. The application was tested on a set of colour retina images, taken by fundus camera. The final application is supposed to run on a digital signal processor, developed by Texas Instruments. The thesis gives the introduction into biometrics, signal processing and human eye anatomy.
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Generation of Skin Disease Effects into Synthetic Fingerprints from SFinGe Generator
Wildmann, Radek ; Drahanský, Martin (referee) ; Kanich, Ondřej (advisor)
This thesis discuss the topic of generation of skin disease effects, psoriasis and colagenosis into synthetic fingerprints from SFinGe generator. Thesis includes theoretical as well as practical approach of the topic including implementation design, program implementation and experiment results. SFinGe approach is used to generate fingerprints. Python (2.7.6) is used to implement algorithm for image processing and generating disease symptoms with OpenCV, Matplotlib, NumPy and SciPy libraries. For results evaluation, NFIQ standard and Oravec approach are used. The application is able to generate fingerprint image with symptoms of psoriasis or colagenosis, therefore it can be used for futher research with biometric systems.
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Analysis of Facial Development Based on Anthropometric Properties
Oravec, Dávid ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
This bachelor thesis deals with anthropometry of human face, anthropometric landmarks, which are used to determine the distances and various relations between them. Our body is aging and consequently the position of anthropometric points is changing. The aim of this work is to determine anthropometric landmarks from photo of the human face and then to analyze the given face and how it develops over time. The model for facial landmark detection was trained and selected points which will be used to determine facial indices were chosen. Indices are used to find out how the face is evolving over time. Based on experiments we observe how the faces of men and women are changing over time.
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Algorithmic Solution for Determining the Age of a Person Based on 2D Photography Using Artificial Intelligence
Bednář, Pavel ; Goldmann, Tomáš (referee) ; Drahanský, Martin (advisor)
Automated person's age estimation from a facial image is one of the challenges in the field of artificial intelligence and machine learning. Age estimation is often a non-trivial complexity for a person, unlike other biological characteristics such as determining gender or race. Information about an individual's age is very important for certain situations. For example, when committing an offense or crime, the amount of the sentence is co-determined by age. This information can also be used in the analysis of customers of a commercial entity and the subsequent adjustment of the offer. The aim of this work is to be able to extract his age from a photograph of a human face. The algorithm consists of two modules. If the first module says that the person is under 14 years old, the image will go to the second module. Furthermore, another version of the algorithm is proposed with an added module focused on selected facial features. In all modules transformations are performed on the image and their results are averaged. Finally, the algorithm is evaluated on standard datasets for age estimation and compared with state-of-the-art methods in this area.
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Control of Positionable Platform for Eye Centering in Image
Magdolen, Patrik ; Semerád, Lukáš (referee) ; Drahanský, Martin (advisor)
Ophthalmology is a branch of medicine that deals with the anatomy, physiology and diseases of the eyeball and orbit. An ophthalmic device for the acquirement and recognition of a human eye characteristics was created by researchers from Faculty of Information Technology. This device can be used either for biometric purposes or for medical purposes as a support diagnostic device. To achieve proper functionality, device must be able to adjust platform position in order to align optic camera with patient's eye. The main focus of this thesis is to design and implement an algorithm for eye centre localisation based on images of the patient's face. The first part of this thesis describes general methods for eye localisation and proposed solution. To achieve requested accuracy, combination of multiple methods is used with adjusted parameters based on platform's features. The second part describes implementation of proposed solution as well as platform control. Multiple databases were used for training and testing of the algorithm. The third part summarises performed experiments. The proposed algorithm was implemented in the C++ language, using OpenCV library. Accuracy and speed of proposed algorithm are suitable for developed platform. In the end, the results are discussed and further improvements are proposed.
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SMS Encryption for Mobile Communication
Lisoněk, David ; Bouška, Petr (referee) ; Drahanský, Martin (advisor)
This thesis deals with encryption of short text message (SMS) in mobile communication. Introduction is dedicated to overview of the parts of GSM radiotelephone nets and SMS messages transfer . Next chapter is reserved for description of cryptographic methods especially symetric and asymetric encryptografic aproaches. A design of a SMS messages encryption and decryption techniques is in next. For SMS encryption and sign, there is used the asymetric cypher RSA. Encryption use OAEP padding schema. The public key is saved in certificate. The Symbian OS has been choosen as a suitable platform for programming of mobile devices.
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Reconstruction of Damaged Parts of Fingerprint Image
Halva, Vladislav ; Drahanský, Martin (referee) ; Kanich, Ondřej (advisor)
This bachelor thesis deals with the reconstruction of damaged fingerprint areas. The main goal is the design and implementation of an algorithm for the reconstruction of these regions. The designed algorithm consists of three main parts. The first part is fingerprint feature extraction and their derivation in damaged areas. The second part is a localization of damaged areas, which is based mainly on the structure of papillary lines. The last part is the damaged areas reconstruction itself. Gabor filter is used in this part of the process. The algorithm is implemented in C++ using the OpenCV library. An analysis of the reconstruction success rate is done afterwards. It is at first evaluated using the difference of quality between the input and processed fingerprint image, estimated by NIST NFIQ 2.0 and one other alternative tool for fingerprint image quality evaluation. The next step is a manual evaluation of the reconstruction success rate in various types of damaged areas.
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Program for Training of Dactyloscopic Experts
Bartoň, Jan ; Drahanský, Martin (referee) ; Lodrová, Dana (advisor)
This work deals with the design project and the creation of user interface of a programme for the training of dactyloscopy experts. The first chapters describe historical and technical evolution of dactyloscopy. Then the work explains the methods and concepts necessary for understanding and elemental orientations in determination of fingerprints. The final chapters present a proposition of possibilities in how to obtain and represent the results in a comprehensible form. The conclusion of the work is dedicated to tests and evaluation of the results.
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Retinal Blood Vessel Segmentation
Nemčeková, Barbora ; Drahanský, Martin (referee) ; Kavetskyi, Andrii (advisor)
The retina is an important part of the human eye. Incident light is processed here and moreover, it plays an essential role in diagnosing various diseases. Its early diagnostics can prevent serious consequences, such as blindness. The most common retinal diseases include diabetic retinopathy, as a consequence of diabetes, and age-related macular degeneration. Automatic retinal vessels segmentation facilitates and speeds up the work of an ophthalmologist. This work focuses on retinal blood vessels segmentation and its further classification into thin and thick vessels. The proposed algorithm is based on morphological operations, k-means clustering, and Frangi's algorithm. Evaluation of the proposed method was performed on two publicly available datasets - Drive and HRF. The results obtained represent 69,89 % for sensitivity, 91,55 % for specificity, and 88,63 % for accuracy. Division of the vessels shows, that on average 21,50 % vessels pixels belong to thick vessels and the rest 78,50 % belong to thin vessels.
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