Visualization on colour based flow vector of thermal image for movement detection during interactive session

Recently thermal imaging is exploited in applications such as motion and face detection. It has drawn attention many researchers to build such technology to improve lifestyle. This work proposed a technique to detect and identify a motion in sequence images for the application in security monitoring system or outdoor surveillance. Conventional system might cause false information with the present of shadow. Thus, methods employed in this work are Canny edge detector method, Lucas Kanade and Horn Shunck algorithms, to overcome the major problem when using thresholding method, which is only intensity or pixel magnitude is considered instead of relationships between the pixels. The results obtained could be observed in flow vector parameter and the segmentation colour based image for the time frame from 1 to 10 seconds. The visualization of both the parameters clarified the movement and changes of pixel intensity between two frames by the supportive colour segmentation, either in smooth or rough motion. Thus, this technique may contribute to others application such as biometrics, military system, and surveillance machine

Performance of an Echo Canceller and Channel Estimator for On-Channel Repeaters in DVB-T/H Networks

This paper investigates the design and performance of an FIR echo canceller for on-channel repeaters in DVB-T/H network within the framework of the PLUTO project. The possible approaches for echo cancellation are briefly reviewed and the main guidelines for the design of such systems are presented. The main system parameters are discussed. The performance of an FIR echo canceller based on an open loop feedforward approach for channel estimation is tested for different radio channel conditions and for different number of taps of the FIR filter. It is shown that a minimum number of taps is recommended to achieve a certain mean rejection ratio or isolation depending on the type of channel. The expected degradation in performance due to the use of fixed point rather than floating point arithmetic in hardware implementation is presented for different number of bits. Channel estimation based on training sequences is investigated. The performance of Maximum Length Sequences and Constant Amplitude Zero Autocorrelation (CAZAC) Sequences is compared for different channels. Recommendations are given for training sequence type, length and level for DVB-T/H on-channel repeater deployment

A Novel Data-Aided Channel Estimation with Reduced Complexity for TDS-OFDM Systems

In contrast to the classical cyclic prefix (CP)-OFDM, the time domain synchronous (TDS)-OFDM employs a known pseudo noise (PN) sequence as guard interval (GI). Conventional channel estimation methods for TDS-OFDM are based on the exploitation of the PN sequence and consequently suffer from intersymbol interference (ISI). This paper proposes a novel dataaided channel estimation method which combines the channel estimates obtained from the PN sequence and, most importantly, additional channel estimates extracted from OFDM data symbols. Data-aided channel estimation is carried out using the rebuilt OFDM data symbols as virtual training sequences. In contrast to the classical turbo channel estimation, interleaving and decoding functions are not included in the feedback loop when rebuilding OFDM data symbols thereby reducing the complexity. Several improved techniques are proposed to refine the data-aided channel estimates, namely one-dimensional (1-D)/two-dimensional (2-D) moving average and Wiener filtering. Finally, the MMSE criteria is used to obtain the best combination results and an iterative process is proposed to progressively refine the estimation. Both MSE and BER simulations using specifications of the DTMB system are carried out to prove the effectiveness of the proposed algorithm even in very harsh channel conditions such as in the single frequency network (SFN) case