Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates

Real-time mean-shift based tracker for thermal vision systems

Real-time object tracking is the critical task in many computer vision applications such as surveillance, object-based video compression, or driver assistance. The most challenging issues encountered in visual object tracking are cluttered background, noise, occlusions and appearance change off tracked objects. The whole process of object tracking is made with component called tracker. In typical visual tracker we can distinguish two major components. One is responsible for target representation and localization, while second is responsible for filtering and data association with respect to object dynamics. Visual tracker have to cooperate with some other components. To start tracking procedure interesting object have to be detected. Detection algorithm have to point interesting object out for the tracking algorithm. This component is not always necessary. There are systems where interesting object is pointed by the system operator. Results of tracking are also used in some reasoning and decision taking component. Tracking algorithms can be divided in four broad categories: 1. Gradient-based methods locate target objects in the subsequent frame by minimizing a cost function. 2. Feature-based approaches use features extracted from image attributes such as intensity, color, edges and contours for tracking target objects. 3. Knowledge-based tracking algorithms use apriori knowledge of target objects such as shape, objec

The effect of oxidant on leaching lead from copper concentrate

W artykule podano wyniki doświadczeń laboratoryjnych ługowania ołowiu z koncentratu miedziowego za pomocą octanu amonu. Przebadano wpływ dodatku nadtlenku wodoru do roztworu ługującego na stopień ługowania ołowiu z koncentratu. Proces prowadzono przez 60 minut w temperaturze 293 K, stosując roztwory octanu amonowego o stężeniu 10% i 40% wagowych.This article presents results of laboratory experiments of leaching lead from copper concentrate with ammonium acetate. The effect of addition of hydrogen peroxide to the leaching solution on the rate of lead leaching from copper concentrate was studied. The process was carried out for 60 minutes at 293 K, in 10 and 40 percent (by weight) ammonium acetate solutions

Hardware implementation of tracking algorithm on thermovision images in FPGA

W artykule przedstawiono algorytm śledzenia obiektów na obrazach termowizyjnych za pomocą zmodyfikowanej metody SSD oraz propozycję jego implementacji sprzętowej w module programowalnym FPGA. Zastosowanie technologii FPGA pozwoliło na zastosowanie kilku technik przyspieszania obliczeń. Moduły realizujące algorytm zostały zaprojektowane tak, by obliczenia prowadzony były w trybie pipeliningu. Ponadto w celu zwiększenia szybkości działania algorytmu zastosowane zostało zrównoleglenie obliczeń. W artykule opisano architekturę zaprojektowanego systemu przetwarzania obrazów i śledzenia obiektów na obrazie metodą SSD.In the article the architecture of hardware implementation of SSD tracking algorithm for thermal images is proposed. Object tracking is a process of finding chosen object on the following frame using knowledge about its position in previous frames [1, 3]. Gradient based methods like Sum-of-Squared-Differences (SSD) localize targets by analyzing differences between consequent frames. Finding target movement is performed by searching minimum of cost function in space and time. Cost function in this approach is a sum of squared differences. Sum of squared differences coefficient is a measure of difference between two fragments of images and equals (1). If searched object was detected at point (x, y) in previous frame, finding its location in following frame would mean finding (u, v) for which SSD coefficient is the smallest. The picture fragment centered at (x, y) with size equal to the size of the object is treated as the object model. Point (u, v) will then be a centre of the object that is the most similar to the model. This object in new frame is the one found by the SSD algorithm. SSD object estimation is not always reliable, when object is obscured or noised. To distinct reliable position estimation from noisy one the special SSDVar (2) coefficient was developed. The algorithm to calculate SSD coefficient for set of image fragments was proposed to be implemented in hardware, using parallel computation for every compared image fragments. The architecture of parallelized SSD computation unit is shown on Fig. 4 and Fig. 5. Main parts of computation unit were simulated in Quartus II environment

The enhanced sum of squared differences method for tracking objects in thermal vision pictures

Śledzenie obiektów jest coraz częściej stosowane w systemach wizyjnych używanych do ochrony mienia, kompresji sekwencji wideo czy w produkcji filmowej. Śledzenie obiektu polega na wyznaczeniu jego położenia na pewnej klatce obrazu, na podstawie znajomości jego położenia na poprzednich klatkach. Zadanie to jest szczególnie utrudnione, jeśli wymagany jest krótki czas wykonywania śledzenia. Ponadto w obrazie termowizyjnym nie można śledzić obiektów za pomocą metod stosowanych dla obrazu widzialnego. W artykule został omówiony nowy algorytm śledzenia obiektów w obrazie termowizyjnym polegający na modyfikacji metody Sum of Squared Differences.Real-time object tracking is a critical task in many computer vision applications such as surveillance, object based video compression, or driver assistance. Object tracking is a process of finding a chosen object within a frame using the knowledge about its position in the previous frames. The most challenging issues encountered during visual object tracking are cluttered background, noise, occlusions and change in appearance of the tracked objects. This task is even more challenging when tracking is time constrained, and evaluation of the object position has to be performed in real-time. There exist many techniques for tracking objects but most of them are implemented in colour vision systems. Tracking algorithms for thermal vision systems have not been investigated well yet. This paper deals with adopting the sum of squared differences (SSD) tracking algorithm to thermal vision image sequences. Gradient based tracking methods, like SSD, evaluate target transition by finding changes between two consequent frames. The changes are estimated with gradients in space and time by finding the smallest SSD coefficient. This method is of relatively low computational complexity and can be used in real-time system. In the paper the enhanced SSD algorithm is presented. The enhancement consists in the conditional model update based on the SSDVar coefficient. There is also presented an experiment in which the traditional and enhanced SSD methods are compared

Thermovision system for aircraft landing

The paper presents the developed multispectral optoelectronic aircraft landing assistance and data transmission system for flight control. The purpose of the system is to provide information about the landing aircraft (in the day, at night and in the haze), such as the location of the aircraft in the runway axis, altitude, distance to touchdown and the condition of the plane components like landing gear etc. The system employs two infrared cameras working in spectral range of 3-5 µm and 8-12 µm and a video camera module. The system was tested in laboratory and in the field

Thermal camera system integrated into firefighter helmet

The paper presents a firefighter helmet with integrated thermal camera system, OLED display, sensors for monitoring the vital signs of a firefighter-rescuer and communication system for transmitting such data as live thermal video streaming, body temperature, heart rate and ambient temperature. The developed helmet, apart from its typical function as personal protection device against threats associated with firefighter’s work, also provides enhanced capability of carrying out rescue missions in low-visibility scenarios, thus increasing the safety of a firefighter itself

Moduł do przetwarzania obrazu z mikrobolometrycznej kamery podczerwnieni z zastosowaniem układu FPGA

In article a digital system for high resolution infrared camera control and image processing is described. The camera is built with use of bolometric focal plane array of size 640 by 480 detectors. Designed module controls the microbolometer Focal Plane Array (FPA), performs non-uniformity correction, bad pixel mapping and controls the process of displaying the thermal image. The system was designed in such a way, that signal processing algorithms, needed for specific tasks, can be implemented in it without hardware modifications. It was achieved by the application of a FPGA device and microprocessor unit, which both can be re-programmed inside the system. This scientific work is funded as a development project from science funds for years 2009-2011.W artykule opisano uniwersalny cyfrowy system sterowania i przetwarzania dla kamery termowizyjnej z matrycowym detektorem bolometrycznym rejestrującym promieniowanie w zakresie widmowym w przedziale 8÷12 μm. Najważniejszym zadaniem systemu jest odczytanie sygnałów z poszczególnych detektorów matrycy oraz korekcja wartości wzmocnienia i napięcia przesunięcia charakterystyki czułości dla każdego detektora matrycy. Następnym zadaniem jest przetworzenie analogowych sygnałów z matrycy na postać cyfrową i ich zamiana na obraz termiczny. Dane odczytane z matrycy są przekazywane do następnych modułów kamery termowizyjnej za pomocą magistrali danych obrazowych. Układ sterowania odczytem jest ponadto wyposażony w magistralę sterowania za pomocą, której można ustawić parametry generowanych sygnałów dla matrycy mikrobolometrycznej. Parametry, które mogą podlegać zmianie to liczba obrazów odczytywanych w ciągu sekundy oraz czas całkowania sygnału z detektorów. W kolejnych modułach przetwarzania obrazu dokonywane są operacje takie jak np. korekcja niejednorodności detektorów matrycy, wykrywanie i usuwanie wadliwych pikseli, zaawansowane metody poprawy jakości obrazu, metody wspomagające wykrywanie i identyfikację obiektów. Dzięki zastosowanej architektury systemu możliwa jest adaptacyjna zmiana działania systemu bez konieczności stosowania znaczących zmian sprzętowych. Praca naukowa finansowana ze środków na naukę w latach 2009-2011 jako projekt rozwojowy

The method for vision and infrared image processing in a single digital system

W systemach obserwacyjnych coraz częściej stosuje się zespół kamery termowizyjnej i kamery wideo. Znaczna różnica w standardzie rejestrowanych obrazów sprawia, że ich jednoczesne przetwarzanie jest zadaniem złożonym. W artykule przedstawiono metodę pozwalającą na przetwarzanie obrazu termowizyjnego i obrazu wideo we wspólnym systemie cyfrowym. Zaprezentowane rozwiązanie pozwala na wyświetlanie rejestrowanego obrazu jednocześnie w dwóch różnych standardach wideo. Opracowana metoda została przetestowana i zaimplementowana w sprzęcie.Multisensory systems are often used in security systems for border surveillance and protection as well as in various military systems like fire control systems. In security systems combined infrared and vision cameras are used to increase effectiveness and detection efficiency. The reason for wide use of infrared cameras in many surveillance and industrial areas is registration of an image in the infrared waveband, which provides new information about the observed process. A traditional vision camera works in the visible spectrum and is applied in security systems for face recognition and identification providing evidence to incidents in the monitored area. A system consisting of infrared and visible cameras allows observing the scene in two wavebands merging advantages of both technologies. The image digital processing system must be designed with consideration about differences between infrared and vision images. Images from different cameras, besides different information in the picture, can also have different resolution, frame rate and data width. The paper presents an approach to integrating a video channel with infrared channel despite of different pixel clock frequencies and different resolutions of the cameras. A method for integration of two different image data streams from visual and infrared cameras in a single digital system is presented. Furthermore, a method for providing display functionality on monitors working in two different video standards is proposed. The presented system has been tested an