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

Adaptive spatial mode of space-time and spacefrequency OFDM system over fading channels

In this paper we present a 2 transmit 1 receive (1 Tx : 1 Rx) adaptive spatial mode (ASM) of space-time (ST) and space-frequency (SF) orthogonal frequency division multiplexing (OFDM). At low signal to noise ratio (SNR) we employ ST-OFDM and switch to SF-OFDM at a certain SNR threshold. We determine this threshold from the intersection of individual performance curves. Results show a gain of 9 dB (at a bit error rate of 10-3) is achieved by employing adaptive spatial mode compared to a fixed ST-OFDM, almost 6 dB to fixed SF-OFDM, 4 dB to Coded ST-OFDM and 2 dB to a fixed coded SF-OFDM, at a delay spread of 700 ns