Preprocessing Approach Identifying and Removing Noise which Affects Shape

In this paper, we propose a noise removal approach that significantly improves the performance of sophisticated shape matching techniques. Existing shape matching techniques focus on complex algorithms without giving much consideration to the noise removing preprocessing techniques. These preprocessing techniques can reasonably improve the accuracy where the shapes are affected by cracks. We present a preprocessing approach to identify and remove small cracks and slits in the shape contour. It has been observed that these cracks or slits change the shape altogether in a manner which makes classification of shapes difficult. This technique is simple and effective and may be used to preprocess the images before applying sophisticated shape representation techniques to improve their accuracies. The effectiveness of proposed preprocessing approach is verified using publicly available shape datasets.