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Automatic Photography Categorization
Matuszek, Martin ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This thesis deal with choosing methods, design and implementation of application, which is able of automatic categorization photos based on its content into predetermined groups. Main steps of categorization are described in greater detail. Finding and description of interesting points in image is implemented using SURF, creation of visual dictionary by k-means, mapping on the words through kd-tree structure. Own evaluation is made for categorization. It is described, how the selected steps were implemented with OpenCV and Qt libraries. And the results of runs of application with different settings are shown. And efforts to improve outcome, when the application can categorize right, but success is variable.
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Retinal biometry for human recognition
Sikorová, Eva ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
This master thesis deals with recognition of a person by comparing symptom sets extracted from images of the retinal vessels pattern. The first part includes the insight into biometric issues, the punctual analysis of human identification using retina images, and especially the literature research of methods of extraction and comparison. In the practical part there were realized algorithms for human identification with the method of nearest neighbor search (NS), translation, template matching (TM) and extended NS and TM including more symptoms, for which MATLAB program was used. The thesis includes testing of suggested programs on the biometric database of symptomatic vectors with the following evaluation.
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Protein Classification Techniques
Dekrét, Lukáš ; Zendulka, Jaroslav (referee) ; Burgetová, Ivana (advisor)
Main goal of classifying proteins into families is to understand structural, functional and evolutionary relationships between individual proteins, which are not easily deducible from available data. Since the structure and function of proteins are closely related, determination of function is mainly based on structural properties, that can be obtained relatively easily with current resources. Protein classification is also used in development of special medicines, in the diagnosis of clinical diseases or in personalized healthcare, which means a lot of investment in it. I created a new hierarchical tool for protein classification that achieves better results than some existing solutions. The implementation of the tool was preceded by acquaintance with the properties of proteins, examination of existing classification approaches, creation of an extensive data set, realizing experiments and selection of the final classifiers of the hierarchical tool.
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Automatic Selection of Representative Pictures
Bartoš, Peter ; Svoboda, Pavel (referee) ; Polok, Lukáš (advisor)
There are billions of photos on the internet and as the size of these digital repositories grows, finding target picture becomes more and more difficult. To increase the informational quality of photo albums we propose a new method that selects representative pictures from a group of photographs using computer vision algorithms. The aim of this study is to analyze the issues about image features, image similarity, object clustering and examine the specific characteristics of photographs. Tests show that there is no universal image descriptor that can easily simulate the process of clustering performed by human vision. The thesis proposes a hybrid algorithm that combines the advantages of selected features together using a specialized multiple-step clustering algorithm. The key idea of the process is that the frequently photographed objects are more likely to be representative. Thus, with a random selection from the largest photo clusters certain representative photos are obtained. This selection is further enhanced on the basis of optimization, where photos with better photographic properties are being preferred.
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Gesture Recognition
Svoboda, Tomáš ; Mlích, Jozef (referee) ; Hradiš, Michal (advisor)
This Bachelor's thesis is engaged in recognition hand gestures. The advantages and disavantages of various color models for skin color detection are discussed here. Skin is detected by look-up table. Look-up table is created from histogram of skin color and optional from Gaussian distribution, whose parameters are estimated from histogram. Hidden Markov models are used for gesture classification. The HTK toolkit have been used for working with the models. Own decoder of Hidden Markov models based on Viterbi algorithm was created for real-time gesture recognition. Several experiments were accomplished with data sets for 4 gestures. The results of the experiments are very good.
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Web defects classification
Janošík, Zdeněk ; Petyovský, Petr (referee) ; Honec, Peter (advisor)
In this master thesis is described how to design and implement classifier of defects detected during the final stage of production nonwovens. The beginning of the thesis is devoted to the analysis of options for image processing and classification. Followed by the part, where is described process of image segmentation and extraction of feature vector. Description of classifier implementation and table of achieved results of classification on real images of detected defects.
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Face Features Extraction Methods
Adamček, Ľubomír ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
The face has been one of the most attractive available human biometries for a long time due to it's easy and convenient way to obtain it. Possibilities of it's utilization are broad - from security, through monitoring up to enternainment industry. This work presents the domain of face biometry and analyses 3 extraction methods of facial features - PCA, LBP and HOG. A part of this work is also an efficient implementation of these algorithms including GUI designed to experiment with this implementation and to evaluate its performance on a set of images capturing people in various conditions.
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Detection and Recognition of Traffic Signs
Vránsky, Radovan ; Beran, Vítězslav (referee) ; Herout, Adam (advisor)
This bachelor thesis is about different methods of detection and recognition of traffic signs in pictures. The introduction several of these methods are described and their use is demonstrated. In the next part of the thesis, the implementation of the detection and recognition of traffic signs with the use of Support Vector Machine is described in detail. It also describes the method of creating of the dataset or different models describing this dataset. In the conclusion the method is evaluated.
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Processing of User Reviews
Cihlářová, Dita ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
Very often, people buy goods on the Internet that they can not see and try. They therefore rely on reviews of other customers. However, there may be too many reviews for a human to handle them quickly and comfortably. The aim of this work is to offer an application that can recognize in Czech reviews what features of a product are most commented and whether the commentary is positive or negative. The results can save a lot of time for e-shop customers and provide interesting feedback to the manufacturers of the products.
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Attacking biometric hashing via optimization techniques
Mlčáková, Kristýna ; Mokrý, Ondřej (referee) ; Rajmic, Pavel (advisor)
The thesis deals with biometric hashing, which is a two-factor authentication method that combines a secret key with biometric data in order to create a secure biomeric template for authentication purposes. The thesis first discusses the theoretical aspects of this issue and then focuses on the implementation of this concept. The paper also describes attacks on biometric hashing systems that are subsequently implemented. Practically performed attacks are based on the assumption that the attacker knows the user’s secret key and biohashes stored in the database. Two methods of attacks are applied. These methods are able to reconstruct the biometric data of an authorized user and related biohashes. Methods are based on 1-bit compressive sensing approach. The aim of the thesis is to evaluate the effectivity of the attacks on biometric hashing systems and to make a conclusion about the security of such systems.
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