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.

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.

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.

Abstract. The article presents the concept and implementation of an algorithm for detecting and counting vehicles based on optical flow analysis. The effectiveness and calculation time of three optical flow algorithms (Lucas-Kanade, Horn-Schunck and Brox) were compared. Taking into account the effectiveness and calculation time the Horn-Schunck algorithm was selected and applied to separating moving objects. The authors found that the algorithm is effective at detecting objects when they are subject to binarisation using a fixed threshold. Thanks to the specialized software the results obtained by the algorithm were compared with the manual ones: the total vehicle detection and counting rate achieved by the algorithm was 95,4%. The algorithm is capable to analyse about 8 frames per second (Intel Core i7 920, 2.66 GHz processor, Win7x64).

Thermography is a technology that enables recognition of objects in the specific area. The goal of using thermographic techniques for ironworks is to diagnose electrical equipment. These techniques can be also use to increase safety and quality control in ironworks. Faulty equipment can be dangerous for engineers. Article describes the method of the recognition of imminent failure states of synchronous motor. Thermal images of the stator are used for an analysis of electrical machine. Researches of image processing techniques have been carried out for three states of motor. Proposed approach uses patterns recognition. Using of medial axis transformation and classifier based on words gave good results. In the future electrical machines and metallurgical equipment will use diagnostic systems based on recognition of thermal images.Keywords: Electrical fault detection, Pattern analysis, Thermal images, Synchronous motor, classifier based on words Termografia jest technologią, która umożliwia rozpoznawanie obiektów w określonym obszarze. Celem używania technik termograficznych dla hut jest diagnozowanie sprzętu elektrycznego. Te techniki mogą być również używane do zwiększenia bezpieczeństwa i jakości kontroli w hutach. Wadliwy sprzęt może być niebezpieczny dla inżynierów. Artykuł opisuje metodę diagnostyki stanów przedawaryjnych silnika synchronicznego. Obrazy cieplne stojana są używane do analizy maszyny elektrycznej. Badania technik przetwarzania obrazu zostały wykonane dla trzech stanów silnika. Proponowana metoda używa rozpoznawania wzorców. Użycie transformacji medialnej osi i klasyfikatora opartego na słowach dawało dobre wyniki. W przyszłości maszyny elektryczne i sprzęt hutniczy będą używać systemów diagnostycznych opartych na rozpoznawaniu obrazów cieplnych.