The Optimal Template Automatic Extracting Strategy Based on Edge Run-Length Encoding Index for Image Mosaic

Image measurement based on machine vision is a promising method for the precise measurements of machine parts. As for a large sized work piece that exceeds the FOV (field of view) of the camera, image mosaic must be performed to acquire the panorama of the work piece. The problematic behavior of image mosaic is the contradiction between the precision of mosaic and the complex of algorithm adopted. Image mosaic based on template matching is an effective method for its´ high precision. However, the robustness and complexity of the algorithm depend largely on the selected template. The optimal template pick-up strategy using run length encoding index was proposed and it made a breakthrough in the robustness and speed of template matching algorithm. The optimal template contains image characteristics as much as possible while only the pixels which have edge character and distinct gray value changes participate in the matching operation. Both the precision and speed of template matching algorithm were improved remarkably.