| Extraction of lines and curves from images is one of the most important and fundamental tasks in machine inspection and computer vision in general. Among all the techniques in detecting lines and curves, the Hough Transform (HT) method is outstanding in its ability to cope effectively with noise, gaps in outlines and even partial occlusion.; In spite of this superb recognition ability, the HT method is still not widely used in real time applications due to its disadvantage of being extremely computationally intensive. One solution to this problem is to find an architecture for parallel processing.; An original method of higher order curve detection using the straight line Hough Transform is presented. This scheme is possible because curves in an image can be approximated by small straight line segments. By combining the straight line HT mapping scheme with an associative memory (AM), the method can discriminate and identify between different curves. Curves such as circles, ellipses and parabolas have been studied.; This method is computationally very efficient and may yield to hardware implementation, thus making it possible to use the Hough Transform in fast real time applications. The system consists of a parallel analog mapping from image plane to parameter plane and an AM pattern classifier. |
