{'fraction_non_alphanumeric': 0.018656716417910446, 'fraction_numerical': 0.0018656716417910447, 'mean_word_length': 5.202312138728324, '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}}
A hierarchical semantic video object tracking algorithm using mathematical morphology

In this paper, we propose a hierarchical segmentation method for tracking a semantic video object using mathematical morphology and watershed algorithm. At each hierarchy, we perform 3 basic steps: First, we extract markers on the simplified current frame. Second, region growing by a modified watershed algorithm is performed to get the segmented regions for the current frame. Third, we classify the regions into 3 categories, i.e., inside, outside and uncertain regions, by comparing the region pdf value with the predetermined threshold value. The region pdf value is acquired by the proposed pdf map which is calculated from a motion field estimated in forward direction. For the remaining uncertain regions at the end of a hierarchy, the above three steps are repeated at the lower hierarchy with less simplified frames until every region is decided to a certain region. The proposed algorithm provides prospective results in video sequences such as Miss America, Clair and Akiyo