Study On Image Autofocusing System And Measuring Techniques

Along with development of technology at very fast speed, people are focused popularly on accurate autofocusing and measurement in digital imaging system. The application of techniques of autofocusing and measurement is more and more important. And it is the significance that autofocusing and measurement should ulteriorly enhance precision and speed of measurement and ulteriorly improve extent of automatization and decrease labour intensity.On the basis of current investigation of both the domestic and foreign and current level of development, and contraposing difficulties and keys of autofocusing and measurement, this paper brings forward system of autofocus and measurement based on techniques of image processing of CCD .This system possesses merits of fast speed,high precision,small bulk and large dynamic range.It is able to carry out needs of fast, accurate, large range autofocusing and requests of noncontact and online measurement of workpiece face runout. The system possesses dynamic range of scores of millimeters and focused time of 5 seconds and repeatability of 7 microns.This paper takes the sum of the square of gray difference as the criteria of evaluation function which image is or not focused and takes an effective searching way of autofocusing based on threshold value and curve fitting. This way enhances effectively speed and precision of autofocusing. Least square method is used to eliminate linearity errors of system as result of asymmetric illumination and fitting. Averaging method of neighborhood and medium filtering method are used to effectively overcome thermionic noise as result of courses of image transferring, gathering and quantization and so on.In the course of measurement of workpiece face runout, variance method of the most species based on separability and image edges distilling based on morphology and Marr filtering based on edges segmentation are used to enhance effectively accuracy of image segmentation and edges distilling. Accuracy of measurement of face runout is enhanced effectually by use of least square method of compressing rectangle fitting edge of image and transforming of DFT.