{'fraction_non_alphanumeric': 0.014522821576763486, 'fraction_numerical': 0.0, 'mean_word_length': 5.5646258503401365, '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}}
An iterative parsing approach for contour fragments

This paper presents an approach for linking edge points into contour fragments, each of which is an ordered point sequence. In the problem of shape-based object detection, we investigate what characteristics of the contour fragments representation influence the detection performance. It is observed that if interest objects are represented by limited number of contour fragments, with moderate count of noisy points (not belonging to interest objects) brought in, the detection algorithm can reliably obtain interest objects. For this purpose, we propose to iteratively extract a pair of points which preserves the farthest geodesic distance in each connected component of edge map. We conduct experiments on the ETHZ dataset and compare with other typical methods for generating contour fragments. Experimental results demonstrate that the proposed approach outperforms some existing ones in object detection.