A high precision edge detection method for the blurred image in motion measurement

The motion measurement based on machine vision has been more and more widely used in robots, object tracking and other fields. However, the relative motion between camera and object often causes images blurred, which decreases the reliability of detection. To improve the detection accuracy of the motion-blurred images edges, a comprehensive method is proposed. By analyzing the grayscale distribution of the object images in different motion directions, we used different methods to enhance the low frequency sub-band images which were obtained by wavelet transform. The subpixel edge detection method based on cubic spline interpolation was applied to detect the edges of the blurred and enhanced images, respectively. Experimental results show that the proposed method avoids the misdetection of the blurred images edges, and obtains higher edge detection accuracy.