{'fraction_non_alphanumeric': 0.019153225806451613, 'fraction_numerical': 0.0010080645161290322, 'mean_word_length': 4.841176470588235, '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}}
Rule-based system for region segmentation improvement in stereovision

The aim of this work is to develop a method to improve the region segmentation of images by considering each image separately and taking into account the results of the matching process. The method is carried out in several steps. First, an initial region segmentation is computed by using a split-and-merge algorithm cooperating with an edge extractor. Then, a rule-based system is used in order to improve the initial region segmentation. In the second step of the method, the regions of the images are matched by an iterative algorithm; only the reliable matches are performed and for this reason, numerous regions are left unmatched. Then, these regions are treated by another rule-based system by comparing the homologous regions on each image. Both the image segmentation and the matching results are improved at the same time making easier the 3-D reconstruction of the facets corresponding to the matched regions.