An improved contour-based thinning method for character images

Digital skeleton of character images, generated by thinning method, has a wide range of applications for shape analysis and classification. But thinning of character images is a big challenge. Removal of spurious strokes or deformities in thinning is a difficult problem. In this paper, we propose a contour-based thinning method used for performing skeletonization of printed noisy isolated character images. In this method, we use shape characteristics of text to get skeleton of nearly same as the true character shape. This approach helps to preserve the local features and true shapes of the character images. As a by-product of our thinning approach, the skeleton also gets segmented into strokes in vector form. Hence further stroke segmentation is not required. Experiment is done on printed English, Bengali, Hindi, and Tamil characters and we obtain much better results comparing with other thinning methods without any post-processing.

► Removal of spurious strokes or shape deformation in thinning is a difficult problem.
► We address a contour-based thinning method used for printed noisy isolated character images.
► We use shape characteristics of text to get skeleton of nearly same as the true character shape.
► This approach helps to preserve the local features and true shapes of the character images.
► Experiment is done on printed English, Bengali, Hindi, and Tamil isolated character images.