Automated shape recognition in noisy environments based on morphological algorithms

Automatic shape recognition using morphological operators has proved to be an effective approach to the problem of shape recognition. We present the problem of shape recognition in noisy environments as that of the problem of recognizing imperfect shapes. The method we present in this paper does not require the use of all possible variations of a shape. Instead, this method employs a priori known shape information as a basis for structuring elements, transforms objects into structuring elements, then uses the structuring elements in a hit-or-miss operation to find the location of the shape being recognized. The choice of structuring elements is critical. The resulting image after the hit or-miss operation contains a set of points which indicate the locations of the target shape. Each occurrence of this target shape is represented by one point, or a small cluster of points within a known disk. A number of examples illustrating the process of recognizing imperfect shapes show that, even though the noise environment changes the appearance of the shapes to be recognized in images, our method provides a fast and accurate solution.