Real-time crowd density estimation using images

This paper presents a technique for real-time crowd density estimation based on textures of crowd images. In this technique, the current image from a sequence of input images is classified into a crowd density class. Then, the classification is corrected by a low-pass filter based on the crowd density classification of the last n images of the input sequence. The technique obtained 73.89% of correct classification in a real-time application on a sequence of 9892 crowd images. Distributed processing was used in order to obtain real-time performance. © Springer-Verlag Berlin Heidelberg 2005.

Detecção de bordas em imagens digitais através de um processo de difusão anisotrópica não linear

The edges detection model by a non-linear anisotropic diffusion, consists in a mathematical model of smoothing based in Partial Differential Equation (PDE), alternative to the conventional low-pass filters. The smoothing model consists in a selective process, where homogeneous areas of the image are smoothed intensely in agreement with the temporal evolution applied to the model. The level of smoothing is related with the amount of undesired information contained in the image, i.e., the model is directly related with the optimal level of smoothing, eliminating the undesired information and keeping selectively the interest features for Cartography area. The model is primordial for cartographic applications, its function is to realize the image preprocessing without losing edges and other important details on the image, mainly airports tracks and paved roads. Experiments carried out with digital images showed that the methodology allows to obtain the features, e.g. airports tracks, with efficiency.

Utilização de equações diferenciais parciais no tratamento de imagens orbitais

Pós-graduação em Ciências Cartográficas - FCT

Aplicaciones de filtrado adaptativo LMS para mejorar la respuesta de acelerómetros

El proyecto, “Aplicaciones de filtrado adaptativo LMS para mejorar la respuesta de acelerómetros”, se realizó con el objetivo de eliminar señales no deseadas de la señal de información procedentes de los acelerómetros para aplicaciones automovilísticas, mediante los algoritmos de los filtros adaptativos LMS. Dicho proyecto, está comprendido en tres áreas para su realización y ejecución, los cuales fueron ejecutados desde el inicio hasta el último día de trabajo. En la primera área de aplicación, diseñamos filtros paso bajo, paso alto, paso banda y paso banda eliminada, en lo que son los filtros de butterworth, filtros Chebyshev, de tipo uno como de tipo dos y filtros elípticos. Con esta primera parte, lo que se quiere es conocer, o en nuestro caso, recordar el entorno de Matlab, en sus distintas ecuaciones prediseñadas que nos ofrece el mencionado entorno, como también nos permite conocer un poco las características de estos filtros. Para posteriormente probar dichos filtros en el DSP. En la segunda etapa, y tras recordar un poco el entorno de Matlab, nos centramos en la elaboración y/o diseño de nuestro filtro adaptativo LMS; experimentado primero con Matlab, para como ya se dijo, entender y comprender el comportamiento del mismo. Cuando ya teníamos claro esta parte, procedimos a “cargar” el código en el DSP, compilarlo y depurarlo, realizando estas últimas acciones gracias al Visual DSP. Resaltaremos que durante esta segunda etapa se empezó a excitar las entradas del sistema, con señales provenientes del Cool Edit Pro, y además para saber cómo se comportaba el filtro adaptativo LMS, se utilizó señales provenientes de un generador de funciones, para obtener de esta manera un desfase entre las dos señales de entrada; aunque también se utilizó el propio Cool Edit Pro para obtener señales desfasadas, pero debido que la fase tres no podíamos usar el mencionado software, realizamos pruebas con el generador de funciones. Finalmente, en la tercera etapa, y tras comprobar el funcionamiento deseado de nuestro filtro adaptativo DSP con señales de entrada simuladas, pasamos a un laboratorio, en donde se utilizó señales provenientes del acelerómetro 4000A, y por supuesto, del generador de funciones; el cual sirvió para la formación de nuestra señal de referencia, que permitirá la eliminación de una de las frecuencias que se emitirá del acelerómetro. Por último, cabe resaltar que pudimos obtener un comportamiento del filtro adaptativo LMS adecuado, y como se esperaba. Realizamos pruebas, con señales de entrada desfasadas, y obtuvimos curiosas respuestas a la salida del sistema, como son que la frecuencia a eliminar, mientras más desfasado estén estas señales, mas se notaba. Solucionando este punto al aumentar el orden del filtro. Finalmente podemos concluir que pese a que los filtros digitales probados en la primera etapa son útiles, para tener una respuesta lo más ideal posible hay que tener en cuenta el orden del filtro, el cual debe ser muy alto para que las frecuencias próximas a la frecuencia de corte, no se atenúen. En cambio, en los filtros adaptativos LMS, si queremos por ejemplo, eliminar una señal de entre tres señales, sólo basta con introducir la frecuencia a eliminar, por una de las entradas del filtro, en concreto la señal de referencia. De esta manera, podemos eliminar una señal de entre estas tres, de manera que las otras dos, no se vean afectadas por el procedimiento. Abstract The project, "LMS adaptive filtering applications to improve the response of accelerometers" was conducted in order to remove unwanted signals from the information signal from the accelerometers for automotive applications using algorithms LMS adaptive filters. The project is comprised of three areas for implementation and execution, which were executed from the beginning until the last day. In the first area of application, we design low pass filters, high pass, band pass and band-stop, as the filters are Butterworth, Chebyshev filters, type one and type two and elliptic filters. In this first part, what we want is to know, or in our case, remember the Matlab environment, art in its various equations offered by the mentioned environment, as well as allows us to understand some of the characteristics of these filters. To further test these filters in the DSP. In the second stage, and recalling some Matlab environment, we focus on the development and design of our LMS adaptive filter; experimented first with Matlab, for as noted above, understand the behavior of the same. When it was clear this part, proceeded to "load" the code in the DSP, compile and debug, making these latest actions by the Visual DSP. Will highlight that during this second stage began to excite the system inputs, with signals from the Cool Edit Pro, and also for how he behaved the LMS adaptive filter was used signals from a function generator, to thereby obtain a gap between the two input signals, but also used Cool Edit Pro himself for phase signals, but due to phase three could not use such software, we test the function generator. Finally, in the third stage, and after checking the desired performance of our DSP adaptive filter with simulated input signals, we went to a laboratory, where we used signals from the accelerometer 4000A, and of course, the function generator, which was used for the formation of our reference signal, enabling the elimination of one of the frequencies to be emitted from the accelerometer. Note that they were able to obtain a behavior of the LMS adaptive filter suitable as expected. We test with outdated input signals, and got curious response to the output of the system, such as the frequency to remove, the more outdated are these signs, but noticeable. Solving this point with increasing the filter order. We can conclude that although proven digital filters in the first stage are useful, to have a perfect answer as possible must be taken into account the order of the filter, which should be very high for frequencies near the frequency cutting, not weakened. In contrast, in the LMS adaptive filters if we for example, remove a signal from among three signals, only enough to eliminate the frequency input on one of the inputs of the filter, namely the reference signal. Thus, we can remove a signal between these three, so that the other two, not affected by the procedure.

On increasing the effective aperture of antennas by data processing /

Includes bibliographical references (p. 58-59)

The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis

Statistical approaches to study extreme events require, by definition, long time series of data. In many scientific disciplines, these series are often subject to variations at different temporal scales that affect the frequency and intensity of their extremes. Therefore, the assumption of stationarity is violated and alternative methods to conventional stationary extreme value analysis (EVA) must be adopted. Using the example of environmental variables subject to climate change, in this study we introduce the transformed-stationary (TS) methodology for non-stationary EVA. This approach consists of (i) transforming a non-stationary time series into a stationary one, to which the stationary EVA theory can be applied, and (ii) reverse transforming the result into a non-stationary extreme value distribution. As a transformation, we propose and discuss a simple time-varying normalization of the signal and show that it enables a comprehensive formulation of non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with a constant shape parameter. A validation of the methodology is carried out on time series of significant wave height, residual water level, and river discharge, which show varying degrees of long-term and seasonal variability. The results from the proposed approach are comparable with the results from (a) a stationary EVA on quasi-stationary slices of non-stationary series and (b) the established method for non-stationary EVA. However, the proposed technique comes with advantages in both cases. For example, in contrast to (a), the proposed technique uses the whole time horizon of the series for the estimation of the extremes, allowing for a more accurate estimation of large return levels. Furthermore, with respect to (b), it decouples the detection of non-stationary patterns from the fitting of the extreme value distribution. As a result, the steps of the analysis are simplified and intermediate diagnostics are possible. In particular, the transformation can be carried out by means of simple statistical techniques such as low-pass filters based on the running mean and the standard deviation, and the fitting procedure is a stationary one with a few degrees of freedom and is easy to implement and control. An open-source MAT-LAB toolbox has been developed to cover this methodology, which is available at https://github.com/menta78/tsEva/(Mentaschi et al., 2016).

A linearly tunable low-voltage CMOS transconductor with improved common-mode stability and its application to (gm)-C filters

A linearly tunable low-voltage CMOS transconductor featuring a new adaptative-bias mechanism that considerably improves the stability of the processed-signal common,mode voltage over the tuning range, critical for very-low voltage applications, is introduced. It embeds a feedback loop that holds input devices on triode region while boosting the output resistance. Analysis of the integrator frequency response gives an insight into the location of secondary poles and zeros as function of design parameters. A third-order low-pass Cauer filter employing the proposed transconductor was designed and integrated on a 0.8-mum n-well CMOS standard process. For a 1.8-V supply, filter characterization revealed f(p) = 0.93 MHz, f(s) = 1.82 MHz, A(min) = 44.08, dB, and A(max) = 0.64 dB at nominal tuning. Mined by a de voltage V-TUNE, the filter bandwidth was linearly adjusted at a rate of 11.48 kHz/mV over nearly one frequency decade. A maximum 13-mV deviation on the common-mode voltage at the filter output was measured over the interval 25 mV less than or equal to V-TUNE less than or equal to 200 mV. For V-out = 300 mV(pp) and V-TUNE = 100 mV, THD was -55.4 dB. Noise spectral density was 0.84 muV/Hz(1/2) @1 kHz and S/N = 41 dB @ V-out = 300 mV(pp) and 1-MHz bandwidth. Idle power consumption was 1.73 mW @V-TUNE = 100 mV. A tradeoff between dynamic range, bandwidth, power consumption, and chip area has then been achieved.

A rational approach to the synthesis of one-dimensional acoustic filters

The velocity ratio algorithm developed from a heuristic study of transfer matrix multiplication has been employed to bring out the relative effects of the elements constituting a linear, one-dimensional acoustic filter, the overall dimensions of which are fixed, and synthesize a suitable straight-through configuration for a low-pass, wide-band, non-dissipative acoustic filter. The potential of the foregoing approach in applications to the rational design of practical acoustic filters such as automotive mufflers is indicated.

Compact ridged-waveguide bandpass filters and diplexers

A ridged-waveguide diplexer incorporating integrated compact ridged-waveguide filters and a ridged-waveguide T-junction is presented. The compact size of the filter is achieved by integrating of bandpass periodic filter, and a low-pass structure is used in order to suppress spurious responses. Simulation using the mode-matching method has been carried out for ridge-waveguide filters and T junctions and the results are presented. The measured results are in good agreement with the simulated results. (C) 2004 Wiley Periodicals, Inc.

Holistic Design Strategy for High-Selectivity Low-Loss Integrated Millimetre-Wave Image-Reject Filters

To alleviate practical limitations in the design of mm-wave on-chip image-reject filters, systematic design methodologies are presented. Three low-order filters with high-selectivity and low-loss characteristics are designed and compared. Transmission zeroes are created by means of a quarter-wave transmission line (filter 1) and a series LC resonator (filters 2 and 3). Implemented on SiGe, the filters occupy 0.125, 0.064, and 0.079 mm2 chip area including pads. The measured transmission
losses across 81-86 GHz E-Band frequency range are 3.6-5.2 dB for filter 1, 3.1-4.7 dB for filter 2 and 3.6-5 dB for filter 3 where rejection levels at the image band are greater than 30 dB.

Preliminary results from the infrared multilayer filters and materials exposed to the space environment on the NASA LDEF mission

With continually increasing demands for improvements to atmospheric and planetary remote-sensing instrumentation, for both high optical system performance and extended operational lifetimes, an investigation to access the effects of prolonged exposure of the space environment to a series of infrared interference filters and optical materials was promoted on the NASA LDEF mission. The NASA Long Duration Exposure Facility (LDEF) was launchd by the Space Shuttle to transport various science and technology experiments both to and from space, providing investigators with the opportunity to study the effects of the space environment on materials and systems used in space-flight applications. Preliminary results to be discussed consist of transmission measurements obtained and processed from an infrared spectrophotometer both before (1983) and after (1990) exposure compared with unexposed control specimens, together with results of detailed microscopic and general visual examinations performed on the experiment. The principle lead telluride (PbTe) and Zinc Sulphide (ZnS) based multilayer filters selected for this preliminary investigation consist of : an 8-12µm low pass edge filter, a 10.6µm 2.5% half bandwidth (HBW) double half-wave narrow bandpass filter, and a 10% HBW triple half-wave wide bandpass filter at 15µm. Optical substrates of MgF2 and KRS-5 (T1BrI) will also be discussed.

New algorithms for synthesized design of optical filters

Chebyshev optical-filter algorithms for low-cost microcomputers have been improved. An offset ripple is now used for better transmission/matching in low-pass stacks. A prototype for narrowband filters is now more general and nearer practicability.

A tunable triode-MOSFET transconductor and its application to g(m)-C filters

A linear, tunable CMOS transconductance stage is introduced. Drain voltage of the input transistor operating in triode region is settled by a regulation loop and a first-order linear relationship between g(m) and a de bias voltage is achieved. In addition to easy tuning, this technique offers circuit simplicity, wide dynamic range, high input and output impedances and low consumption. The transconductor is presented on both single-ended and fully-differential versions. A 3rd-order elliptical low-pass g(m)-C filter with a nominal roll-off frequency of 2MHz is used as one example for the many applications of the proposed transconductor. SPICE data describe circuits performances and filter tunabilily Passband is tuned at a rate of 2.36KHz/mV and good linearity is indicated by a 0.89% THD for an 800mV(p-p) balanced-driven input.

The Use of Almost Linear Phase IIR filters In DFT Modulated Filter Banks for Communication Systems

This paper is on the use and performance of M-path polyphase Infinite Impulse Response (IIR) filters for channelisation, conventionally where Finite Impulse Response (FIR) filters are preferred. This paper specifically focuses on the Discrete Fourier Transform (DFT) modulated filter banks, which are known to be an efficient choice for channelisation in communication systems. In this paper, the low-pass prototype filter for the DFT filter bank has been implemented using an M-path polyphase IIR filter and we show that the spikes present at the stopband can be avoided by making use of the guardbands between narrowband channels. It will be shown that the channelisation performance will not be affected when polyphase IIR filters are employed instead of their counterparts derived from FIR prototype filters. Detailed complexity and performance analysis of the proposed use will be given in this article.

High bandwidth voltage and current control design for voltage source converters

In this paper, two different high bandwidth converter control strategies are discussed. One of the strategies is for voltage control and the other is for current control. The converter, in each of the cases, is equipped with an output passive filter. For the voltage controller, the converter is equipped with an LC filter, while an output has an LCL filter for current controller. The important aspect that has been discussed the paper is to avoid computation of unnecessary references using high-pass filters in the feedback loop. The stability of the overall system, including the high-pass filters, has been analyzed. The choice of filter parameters is crucial for achieving desirable system performance. In this paper, the bandwidth of achievable performance is presented through frequency (Bode) plot of the system gains. It has been illustrated that the proposed controllers are capable of tracking fundamental frequency components along with low-order harmonic components. Extensive simulation results are presented to validate the control concepts presented in the paper.