Research On Robotic Vision Based On Optical Wavelet Transform

In recent years, in industry production, there has limited working surroundings which are high temperature ~. nuclear radiation poisonous gas, it needs more requirements to robot. In order to make high intelligent for robot, we should fit various sensors on robot, the most important of all is visual sensor. The information data of robotic visual system is very large, thus, how to improve the speed of image processing has been the studying topics and is a difficult problem to be overcome. We could achieve the Fourier transform of image and filter in frequency spectrum by using 4f optical system. The author do some studying works in this domain, the main contents are the follows: The author has designed the system of optical wavelet transform, put forward using spatial light modulation of light address and spatial light modulation of electric address to modulate signals of image at one time. LASLM transform the image, which is the object image, into coherent image, this process of read-in and transforming could be finished in a few milliseconds. According to the need, we can input various functions into EASLM by using computer, and the input image multiplied by filter function in the frequency domain, at last, the signal of modulated image is incepted by Charge Coupled Device (CCD) and is processed in next steps. The time of whole processing is almost 100 milliseconds, the speed of image processing could raise a lots times. The main goal of this system based on optical wavelet transform is path tracks of robotic vision, and Haar wavelet has the edge of detection properties, Mexicohat wavelet has the edge of enhancement. Aiming at spatial sampling and quantification, the whole transfer of light path information has been analyzed. The author puts 3 forward using the design of A/D transfer antialiasing prefilters, which has been used in electronics, in the analysis of light path, thus we have theoretic foundation in the design of structure, and analyze quantification noises, which is the Gauss noise. We had gained of the image edge by using computer simulation, it proved feasibility of the optical system design. In the same time, for the low frequent image, II if we select suitable scale of Haar wavelet (or Mexicohat wavelet), we can detect the edge of image, and the noises could be effective restrain.