{'fraction_non_alphanumeric': 0.010123734533183352, 'fraction_numerical': 0.0, 'mean_word_length': 5.3120567375886525, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Skeletonization by Gradient Regularization and Diffusion

This paper describes a skeletonization process for grayscale or color images based on the diffusion of the color gradient vectors by using a simple iterative regularization scheme. We propose to diffuse the original color gradient vectors to obtain the skeleton of the main contrasted objects. Contrary to a distance transform or thinning based skeleton, the gradient vectors diffusion is a straightforward, simple and efficient approach to compute the skeleton, which does not require the localization of the contours curvatures or a distance map. In comparison to other approaches based on potential field functions, our method does not require the segmentation of the objects or the precise localization of the contours. Our approach is very simple to implement and can be applied to natural noisy color images of old documents.