{'fraction_non_alphanumeric': 0.015300546448087432, 'fraction_numerical': 0.0, 'mean_word_length': 5.785185185185185, '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}}
Direction selective vector field convolution for contour detection

Active contour methods are widely used for efficient contour detection. This paper proposes a novel contribution for the Harris based Vector Field Convolution (HVFC) method, using the orientation information of feature points in the image by analyzing the gradient information in the small neighborhood. Based on the orientation information, relevant edges are emphasized and an improved edge map is used in the iterative process. The main advantage of the introduced Directional HVFC (DHVFC) method is the ability of exploiting orientation information for increased contour detection accuracy even in case of high curvature boundaries and strong background clutter. The quantitative and qualitative evaluation and comparison with other state-of-the-art methods show that the additional directional information increases the detection performance.