This paper presents a novel QoS architecture for IEEE 802.11 multihop broadband ad hoc networks integrated with infrastructure. The authors describe its features, including MAC layer measurements, traffic differentiation, and admission control. The modules required by the network elements as well as their integration are also presented. Additionally, the paper presents results which validate its correct operation and prove its superiority over plain IEEE 802.11. The authors are convinced that the proposed solution will provide QoS support for a variety of services in future mobile ad hoc networks.

Many fault diagnostic methods have been developed in recent years. One of them is thermography. It is a safe and non-invasive method of diagnostic. Fault diagnostic method of incipient states of Direct Current motor was described in the article. Thermographic images of the commutator of Direct Current motor were used in an analysis. Two kinds of thermographic images were analysed: thermographic image of commutator of healthy DC motor, thermographic image of commutator of DC motor with shorted rotor coils. The analysis was carried out for image processing methods such as: extraction of magenta colour, binarization, sum of vertical pixels and sum of all pixels in the image. Classification was conducted for K-Nearest Neighbour classifier. The results of analysis show that the proposed method is efficient. It can be also used for diagnostic purposes in industrial plants.

The paper is focused on computing acceleration for hybrid multiprocessor environment. A considered algorithm of content authentication used for digital images and video sequences is implemented and tested in diverse scenarios. Particular goal is capability of the authentication system to process high-resolution digital images or FullHD video sequences in real time. Aim of this work was to explore and take advantage of mixed CPU and GPU processing approach and to investigate possibilities to develop optimal authentication algorithm. Chosen algorithm is based on robust hashes and semi-fragile digital watermarking. Parallelization was achieved using combined OpenCL and OpenMP. Results for time execution were measured for both images and videos. Based on collected results acceleration rates were calculated along with maximum frames per second values for video processing. It can be concluded that parallelism contributes significantly in reducing the computation time by making optimal use of resources. Depending on the test scenario, the rate of acceleration is even thirty times higher comparing with single-core solutions. Introduced modifications reduce execution time while maintaining detection effectiveness.

At the present there are some systems offering pedestrian navigation, but not as many are designated for people with visual impairments. The aim of this study is to present a navigation aid which makes use of a stereoscopy video system, OpenCV library, and general purpose mobile devices. The system is based on algorithms for machine image recognition using a stereoscopy camera rig. It reconstructs the surface of the surrounding scene with high accuracy, and is thus able to provide information about potential obstacles. Our experiments show it is possible to create a real-time solution using a contemporary Android-based mobile phone and two USB cameras.

Infrared thermography can measure the temperature of a surface remotely. In this article authors present a diagnostic method of incipient fault detection. The proposed approach is based on pattern recognition. It uses monochrome thermal images of the rotor with the application of an area perimeter vector and a Bayes classifier. The investigations have been carried out for direct current motor without faults and motor with shorted rotor coils. The measurements were performed in the laboratory. The efficiency of recognition using the area perimeter vector and the Bayes classifier was 100 %. The investigations show that the method based on recognition of thermal images can be profitable for engineers. The proposed method can be applied in mining, metallurgy, fuel industry and in factories where electrical motors are used.

The paper presents an application for generating ground truth data for the purposes of video detection and justifies their use in systems which analyze road traffic videos. The usefulness of described application in the development of video detection software is presented especially during scene configuration and comparative analysis of video detection results versus ground truth data. The latter is possible due to simplicity of the result text files generated in a similar way both by the presented application and by the video detection algorithm. Two example applications of the tool designed to generate ground truth data are presented, together with a discussion of their construction, functionality and abilities. ZBIGNIEW BUBLINSKI, PIOTR PAWLIK AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Biomedical Engineering {buba,piotrus}@agh.edu.pl SEGMENTATION OF OBJECTS IN LOG-POLAR SPACE Abstract. The aim of this work was to develop a simple and fast yet robust algorithm for segmentation of objects in log-polar space. Assuming that some interesting parts of an image are selected by fixation of point of attention, pixels located close to fixation points are transformed to a log-polar space, then edge detection is performed. As a final step, detected edges are processed in a specific manner, which should lead to obtain boundaries of objects. After some smoothing, the detected boundaries are transformed back to a cartesian space and are superimposed on an original image in order to show results of segmentation. The aim of this work was to develop a simple and fast yet robust algorithm for segmentation of objects in log-polar space. Assuming that some interesting parts of an image are selected by fixation of point of attention, pixels located close to fixation points are transformed to a log-polar space, then edge detection is performed. As a final step, detected edges are processed in a specific manner, which should lead to obtain boundaries of objects. After some smoothing, the detected boundaries are transformed back to a cartesian space and are superimposed on an original image in order to show results of segmentation. Joanna Grabska-Chrząstowska *, Przemysław Korohoda **, Zbigniew Pieprzak*** * AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Bioengineering, Al. Mickiewicza 30, 30-059 Krakow, Poland ** AGH University of Science and Technology, Faculty of Computing Science, Electronics and Telecommunications, Department of Electronics, Al. Mickiewicza 30, 30-059 Krakow, Poland *** AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, student of Computer Science, Al. Mickiewicza 30, 30-059 Krakow, Poland **** The work was supported by the AGH-UST grant 11.11.120.612 (first author) and the AGHUST grant 11.11.230.017 (second author) A comparison of the SVM and Neural Networks in signal and image classification **** Introduction Most of the papers that dealt with comparing NN and SVM ended with a conclusion about the superiority of the relatively new technique of the SVM over the NN. The presented paper negates that thesis and depicts that in each presented example backpropagation neural networks, despite their unquestionable faults, is not worse than the currently fashionable SVM (Support Vector Machine) method and even quite often surpasses it. Neural networks managed quite well with an artificially generated problem representing a wide issue of segmentation of crucial objects from the background. The SVM method behaved unstably and reached an acceptable error level with difficulty. This additionally proves advantage of neural networks. It’s hard to think that a set of vectors was too small as 2000 elements were generated, one thousand for each of the two classes. As it is widely known an SVM classifier is unstable on a small-sized training set and SVM's optimal hyperplane may be biased when there are a lot fewer positive feedback samples than the negative ones. Two of the chosen examples had been soundly tested before and the test results had been published just for the neural networks. The earlier work based upon the older versions of the program STATISTICA by StatSoft so a repeated search for optimal networks was performed for the current comparisons using STATISTICA 10 software version. The results for the SVM method were also obtained using the above mentioned STATISTICA 10 software. Moreover, those results were verified in the application performed within the master thesis written by one of the co-authors of this paper. The research was held in the Laboratory of Biocybernetics and Biomedical Engineering. TOMASZ KRYJAK DAMIAN KROL MAREK GORGON 1 AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krakow tomasz.kryjak, ago@agh.edu.pl 2 damians.krol@gmail.com SEGMENTATION OF DISHES FOR THE PURPOSES OF CUSTOMER SERVICE PROCESS AUTOMATION IN A SELF-SERVICE CANTEEN Abstract. The article describes research on dishes segmentation for the purposes of customer service process automation in a self-service canteen. The project assumptions and a prototype test stand are presented. Also the developed empty workspace detection and tray position determination algorithms are discussed. Finally, the chosen dishes segmentation algorithm is described and justified. The article describes research on dishes segmentation for the purposes of customer service process automation in a self-service canteen. The project assumptions and a prototype test stand are presented. Also the developed empty workspace detection and tray position determination algorithms are discussed. Finally, the chosen dishes segmentation algorithm is described and justified. Piotr Pawlik, Zbigniew Bubliński* * AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Automatics and Department of Automatics and Biomedical Engineering, Laboratory of Biocybernetics Image registration using Exponential Chirp Transform Abstract. The of aim article is to check the possibilities of the use of Exponential Chirp transform (ECT) instead of Mellin-Fourier transform (MFT) in areas related to matching patterns problem. In the paper a computational complexity of the algorithm based on ECT in relation to the MFT is estimated. Then the tests for shifted, scaled and rotated images are presented. JAROMIR PRZYBYŁO MIROSŁAW JABŁONSKI 1 AGH University of Science and Technology, Department of Automatics and Bioengineering Mickiewicza Ave., 30, 30-059 Kraków, Poland przybylo@agh.edu.pl , mjk@agh.edu.pl RAY-TRACING-BASED EVENT DETECTION AND 3D VISUALIZATION FOR AUTOMATED VIDEO SURVEILLANCE SYSTEM Abstract. Automated and intelligent video surveillance systems play important role in current home care and facilities security applications. Among many research problems is graphical visualization of semantic messages to the human operator that he can percept information in more natural way. The other essential research question is how to recognize 3D objects and their state on the monitored scene only from their views (2D images from the camera). In this paper we continue our previous work on data fusion in visualization of 3D scene semantic model and propose to recognize events and states of scene objects under surveillance in an automatic way using feedback provided by the renderer. We developed ray-tracing based visualization for surveillance system, that is capable of recognizing object’s state and at the same time present relevant information to the human operator. Automated and intelligent video surveillance systems play important role in current home care and facilities security applications. Among many research problems is graphical visualization of semantic messages to the human operator that he can percept information in more natural way. The other essential research question is how to recognize 3D objects and their state on the monitored scene only from their views (2D images from the camera). In this paper we continue our previous work on data fusion in visualization of 3D scene semantic model and propose to recognize events and states of scene objects under surveillance in an automatic way using feedback provided by the renderer. We developed ray-tracing based visualization for surveillance system, that is capable of recognizing object’s state and at the same time present relevant information to the human operator. Sławomir Mikrut* Agnieszka Moskal* * {Ph.D., Ph.D student} in Department of Geoinformation, Photogrammetry and Environmental Remote Sensing, AGH Kraków {smikrut, amoskal} @agh.edu.pl Selected Aspects of Processing Digital Images Obtained From UAVs Introduction The paper reviews current issues related to UAV flights. The relevant research has been conducted all over the world for years in various scientific research centres. The paper presents selected aspects of processing digital images made with the UAV technology. This paper provides a comparison between a digital image taken from an airborne height and the one made from an UAV level. Results of research show differences in images prepared with similar pixel sizes. The AGH University of Science and Technology in Kraków Department of Geoinformatics,Photogrammetry and Environmental Remote Sensing focuses mainly on geometry and radiometry of recorded images. The UAV technology seems to be highly future-oriented due to its low costs as compared to traditional aerial images taken from classical photogrammetry aircrafts.

Make and Model recognition of cars (MMR) has become an important element of automatic vision based systems. Nowadays, MMR utility is commonly added to traffic monitoring (e.g. Licence Plate Recognition) or law enforcement surveillance systems. Facing the growing significance of Make and Model Recognition of cars we have designed and implemented two different MMR approaches. According to their disparate assumption data of these implementations one is obligated to estimate different car models in milliseconds (with a bit less emphasis placed on its accuracy) while the other is aimed first of all to reach higher classification accuracy. Both the implemented MMR approaches, called Real-Time and Visual Content Classification, respectively, are described in this paper in detail and with reference to other MMR methods presented in the literature. Analyses of their performance with respect to classification accuracy and, in case of the Real-Time approach, to its response time are also presented, discussed and finally concluded.

Abstract The paper presents an application for generating ground truth data for the purposes of video detection and justifies its use in systems which analyze road traffic videos. The usefulness of described application in the development of video detection software is presented - especially during scene configuration and comparative analysis of video detection results versus ground truth data. The latter is possible due to simplicity of the result text files generated in a similar way both by the presented application and by the video detection algorithm. Two exemplary applications of the tool designed to generate ground truth data are presented, together with a discussion of their construction, functionality and abilities.

In this paper, a novel application of Active Appearance Models to detecting knives in images is presented. In contrast to its popular applications in face segmentation and medical image analysis, we not only use this computer vision algorithm to locate an object that is known to exist in an analysed image, but–using an interest point typical of knives–also try to identify whether or not a knife exists in the image in question. We propose an entire detection scheme and examine its performance on a sample test set. The work presented in this paper aims to create a robust visual knife-detector to be used in security applications.

This paper presents a novel approach to object detection in images. We build on the existing work on detecting knives in images, which has previously attempted to solve the problem by using the well-established histogram of oriented gradients (HOG) features. We introduce a new feature set that allows for rapid initial object location in images, and can then be followed by the use of an object specific detector. This approach allows for speeding up the overall detection process, which has been demonstrated on the example of knives, and is in the position of bringing many object detectors closer to real-time execution speeds.

Video transmission and analysis is often utilized in applications outside of the entertainment sector, and generally speaking this class of video is used to perform specific tasks. Examples of these applications include security and public safety. The Quality of Experience (QoE) concept for video content used for entertainment differs significantly from the QoE of surveillance video used for recognition tasks. This is because, in the latter case, the subjective satisfaction of the user depends on achieving a given functionality. Recognizing the growing importance of video in delivering a range of public safety services, we focused on developing critical quality thresholds in license plate recognition tasks based on videos streamed in constrained networking conditions. Since the number of surveillance cameras is still growing it is obvious that automatic systems will be used to do the tasks. Therefore, the presented research includes also analysis of automatic recognition algorithms.

With the growing number of vehicles traveling on public roads, traffic congestion has become a serious problem, resulting in more unpredictable travel times, increased fuel consumption and pollution. Intelligent Transportation Systems (ITS), already being developed by several countries, aim to improve safety, mobility and environmental performance. The goal of the INSIGMA project is to develop a system providing functionality of a typical ITS: real-time traffic monitoring, route planning and traffic control. In this paper we discuss the concepts and solutions developed within the project: dynamic map, sensors – videodetector and GPS tracker – as well as advanced route planning and traffic control algorithms.

Abstract The aim of this work was to develop an algorithm for estimating the waiting time of the cars stopped before the intersection in a traffic flow measurement system (based on optical flow), which does not require the generation of the background and allows to calculation in real time. The proposed method performs analysis in HSV color space - a mask generated from S component is applied to H component. In this way a background - an asphalt and horizontal whitespace - is eliminated. The result of this operation is combined with data from optical flow to detect the vehicles which should be tracked.

Technological progress and decreasing prices of thermographic cameras make their application to monitoring and assessing a technical state of machines is profitable. In article is described the recognition method of imminent failure conditions of synchronous motor. The proposed approach is based on a study of thermal images of the rotor. Extraction of relevant diagnostic information coded in thermal images is important for diagnosing of machine. It can be performed with the use of selected methods of analysis and recognition of images. Studies were carried out for two conditions of motor with the application of quadtree decomposition and backpropagation neural network. The experiments show that the method can be useful for protection of synchronous motor. Moreover, this method can be used to diagnose equipments in steelworks and other industrial plants.

Dynamic Map can be considered a complex information system, composed of spatial databases, storing  static and dynamic data relevant for urban traffic, as well as a set of software modules responsible for data collection, interpretation and provision. The data originates from a network of sensors, both fixed (e.g. video detectors, acoustic sensors, inductive loops) and on-board GPS receivers installed in vehicles. Clients of the Dynamic Map are various software modules  performing such tasks as visualization, route planning, traffic optimization, object tracking and threat detection.  The paper discusses experiences with  an evaluation of the system architecture using the ATAM (Architectural Tradeoffs Analysis Method).  The stages of evaluation comprise describing architectural views, identification of key scenarios and evaluation of risks of their realization.

Intelligent monitoring is currently one of the most prominent research areas. Numerous aspects of such schemes need to be addressed by implementation of various modules covering a wide range of algorithms, beginning from video analytic modules, through quality assessment, up to integrity verification. The goal of this paper is to provide a brief overview of the most recent research results regarding various aspects of the video surveillance processing chain. Specifically, the paper describes a scheme for automatic recognition of the make and model of passing vehicles, the state-of-the-art in quality assessment for recognition tasks, and a system for verification of digital evidence integrity. Concluding remarks highlight the perspectives for further development of the described techniques, and the related research directions.

The paper presents a prototype of a distributed storage, analysis and processing system for multimedia (video, audio, image) content based on the Apache Hadoop platform. The core of the system is a distributed file system with advanced topology, replication and balancing capabilities. Metadata for stored media objects is being managed in a separate database in conformance with well-known metadata models and standards. In addition, the system allows implementation of efficient multimedia data analysis (e.g. face recognition) and processing (e.g. transcoding, digital watermarking) algorithms. Interoperability with external systems, such as the currently-developed Infona is provided by means of an OAI-PMH-compliant interface for metadata harvesting. More in-depth integration is possible by making storage, analysis and processing services available to external entities using the SYNAT integration platform. The article evaluates several important aspects of the proposed distributed repository, such as security, performance, extensibility and interoperability.

This paper deals with practical implementation of semi-fragile watermarking for CCTV footage authentication. Despite the variety of available literature, certain important aspects remain unaddressed. The existing schemes are mostly evaluated against purely academic attacks, and the most practical attacks on information trust remain unaddressed. In this paper, we focus on the collage and the visually insignificant changes attacks, which are of critical importance in the video surveillance scenario. Based on a well-known robust hash function, we design three variants of a digital image authentication scheme. We show that the choice of the watermark embedding technique, although unaddressed in the literature, has critical influence on the tampering detection accuracy. Based on the performed evaluation, we also propose small modifications of the original algorithm, which lead to further improvement of the classification performance.

The large variety of video data sources means variability not only in terms ofincluded content, but also in terms of quality. Therefore, quality assessment pro-vides an additional dimension. The paper describes a comprehensive evaluationexperiment on perceived video quality. Consequently, in summary, 19 200 000video frames will be processed. Given the scale of the experiment, it is setup on a computer cluster in order to accelerate the calculations significantly.This work on Quality of Experience (QoE) is synchronized with that conductedby the Video Quality Experts Group (VQEG), in particular the Joint EffortsGroup (JEG) – Hybrid group project.

The paper reports an application of Architecture-based Tradeoff Analysis Method (ATAM) for early evaluation of the Dynamic Map architecture. The Dynamic Map is a complex information system, composed of spatial databases, storing static and dynamic data relevant for urban traffic, as well as a set of software modules responsible for data collection, interpretation and provision. Due to the complexity of the system, its size and key importance of its services to other subsystems, we decided to perform architecture evaluation using the ATAM method. To facilitate the task new tools supporting ATAM based assessment are proposed: Scenario Influence Matrix and Architectural Decision Matrix. Taking as example an excerpt from the system architecture, we present how they were used during the architecture evaluation. The gathered experience confirm usefulness of the tools, enabling ATAM to help detecting real flaws in a design and identify potential risks.