To overcome the shortages of the developed method for edge detection system based on laser rangefinder (LF), a vision based fast edge information acquiring algorithm for the LF system was proposed. Inverse perspective mapping (IPM) geometrical transform was used to remove the perspective effect on original mature wheat field. The image after IPM transformation was then processed by illumination reduction and contrast enhancement to make the difference between cut and uncut wheat field more evidently, and then transferred into grayscale image. Threshold segmentation method based on histogram was used to convert grayscale image into a binary image, so as to distinguish the cut and uncut wheat. The target points were clustered by adopting cross correlation method on each horizontal scan line in the binary image, and then Hough transform was used to detect the edge line between cut and uncut wheat. The proposed method extended the field of view of the edge detection system based on LF, and owing to the LF system the region of interest area for image processing was well restricted. The results showed an average deviation of 2.35cm, with standard deviation of 3.26. This edge detector providing satisfied performance under different conditions, was an effective edge detection method, and met the demand of recognition for navigation path in wheat harvesting.