Search

This paper proposes an improved amplitude spectrum based Fourier-Mellin algorithm Fourier by studying the nature of the Fourier transform image of the amplitude spectrum and the application of phase spectrum in estimation for image motion vector according to the shortcomings of traditional Fourier-Mellin algorithm when the video image translation, rotation and scaling of the situation exist. Experimental results show that the algorithm can estimate the rotation, translation and other vector parameters of a complicated motion model .The complexity of the algorithm has greatly improved comparing to the traditional Fourier-Mellin algorithm.

A kind of intelligent prompt temperature measurement system was designed which was based on single chip micocomputer. It used the pyroelectric infrared sensor to collect the emitted infrared from human body and to preprocess the signal output of the sensor.Then it could be the conversion signal by the A/D transformation inside SCM .The AVR SCM could control to realize the temperature operation and processing, and send the temperature value to the LCD to display and the voice prompt. Simultaneously, it was added the clock function and over temperature alarm function which made the design more practical. Theoretical basis and the software platform were used in this design of the hardware production and software debugging, and finally the design requirements were realized. The temperature measurement system had the advantages of short response time, non-contact,no interference by temperature field, convenient operation.

In order to enhance the image contrast obtained in fog or haze, an optimized algorithm that based on the modified Retinex module is proposed. According to the defects of the traditional Retinex algorithm, such as high complexity and the halo phenomenon, this method enhanced the image global contrast by modifying the illumination component, and corrected the reflection component using nonlinear function. The experimental results showed that it can increase foggy image clearness quickly, adjust the image brightness effectively and overcome time-consuming drawback of original algorithm that greatly improve the efficiency and speed.

The rotation matrix estimation problem is a keypoint for mobile robot localization, navigation, and control. Based on the quaternion theory and the epipolar geometry, an extended Kalman filter (EKF) algorithm is proposed to estimate the rotation matrix by using a single-axis gyroscope and the image points correspondence from a monocular camera. The experimental results show that the precision of mobile robot's yaw angle estimated by the proposed EKF algorithm is much better than the results given by the image-only and gyroscope-only method, which demonstrates that our method is a preferable way to estimate the rotation for the autonomous mobile robot applications.

According to the disadvantage of the large noises of histogram equalization algorithm, a new adaptive image enhancement algorithm is presented. First, the statistical histogram of the infrared image is done. Then the threshold of plateaus Equalization is calculated and the statistical histogram is modified. Finally the bright values of the pixels of the image are changed. An embedded high speed image enhancement processing system on high performance DSP TMS320DM642 and FPGA was designed. Experimental results with real images shown that the system can improve the contrast of the infrared image, limit the noises of the enhancement image, and effectively enhance the infrared image, the running time of the program is shorter, so it can meet the requirements of real-time in the project.