No abstract

one important issue in machine vision is using automatic attention control methods for monitoring CCTV cameras, in order to enhance the security of people in public. Result of automatic methods such as crowd density estimation can alert the operator in the case of risk probability increasing. In addition to overall crowd density, other parameters such as regional crowd density and the temporal and spatial criteria of each frame of video should be considered to control the operator's attention correctly. For this purpose, according to the gradual change of crowd density and risk probability in daily hours and uncertainty in our knowledge in evaluation of crowded places, we designed a fuzzy decision making system to make decisions about risk probability. The design of this system is based on the fact that the human visual system tends to direct attention to events that happen with low probability. The efficiency of this system is tested on real data and results are presented to demonstrate the practical applications of this system to aid the human operator.

No abstract

The problem of estimating the communication channel affecting a signal, falls into the category of blind system identification. When only one version of the signal is available, this is particularly difficult problem. This paper presents a simple single-channel blind identification of channel impulse response which can be low-pass, band-pass or highpass filter, etc with a FIR filter design in frequency domain. The proposed algorithm is tested with different type of input sources (such as random sequence and speech) using different kind of channels. It was shown that, the proposed algorithm sounds to be more effective for random sequences and can also be used in different application such as loudspeaker or telephone channel equalization.