The mud pulse signal extracting in MWD(Measurement while drilling) was a core technology in the oil drilling developing process. Determining how to accurately define the mud pulse signal starting time was a key issue affecting the decoding accuracy. This paper analyzed the transmission format of down-hole datum and transmission characteristics of mud pulse signal, using a wavelet multi-scale and related de-noising algorithm to extract mud pulse signal. On this basis, according to the characteristics of the underground encoded synchronization signal, It proposed an algorithm based on equal segmentations within a signal period to define the mud pulse signal starting time .The field tests show that the algorithm can accurately define the mud pulse signal starting time and can effectively improve the decoding accuracy and meet the requirements of engineering applications.

The extraction and correct recognition of mud pulse signal in Wireless Measurement While Drilling was a key technology in petroleum drilling process. It determined whether the well course in the petroleum drilling process was right or not. This article has carried out the numerical modeling of mud pulse signal and illustrated its signal feature. In terms of the problems of extraction and recognition of PLM encoded mud pulse signal, it has researched on the noise removing using the Wavelet multi-scale feature recognition and related de-noising algorithms. The location of PLM encoded mud pulse signal was discerned precisely by using the combinational algorithm of local feature and waveform character recognition and laid a foundation for the extraction and accurate recognition of mud pulse signal. Finally, the results of live tests indicate that this arithmetic is simple, useful and conform to the requirements of engineering application.

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License plate recognition technology has been widely used with the development of intelligent traffic system, which studies vehicle identification based on digital image processing technology. This paper presents system design and realization of recognition system for license plate. License plate image is preprocessed by gradation and binaryzation at first, then the image noise caused by dirt is filtered by a mean value method. We adopt horizontal and vertical projection method to locate license plate. Character segmentation and recognition are carried out at last. Test result shows that the method presented has good accuracy, quick speed and strong robustness for realtime application.

A motion object detection method is presented based on Davinci platform. This paper adopts color histogram algorithm to detect moving target, which is operated on TMS320DM6446. In continuous frames, probability distributions of both foreground pixel and background pixel are counted separately to build color histogram. Background probability can be computed based on gauss model. After background separation, we can use median filtering to suppress image noise, detect connected domain, converge foreground pixels to make up of moving object regions and mark them. The results show that the method presented has good accuracy and quick speed for realtime application.