{'fraction_non_alphanumeric': 0.016290726817042606, 'fraction_numerical': 0.0012531328320802004, 'mean_word_length': 5.1461538461538465, '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}}
REGION GROWING COLOUR IMAGE SEGMENTATION APPLIED TO FACE DETECTION

A colour segmentation method is described which is based on a seeded region growing (SRG) segmentation algorithm. First the 3-D histogram in the Lab colour coordinate system is extracted. The histogram bins are then grouped using a hierarchical clustering algorithm. The number of classes can be automatically determined, while a k-means algorithm is used for determining the nal list of dominant colours. The classication according to the dominant colours determines the initial seeds for a region growing segmentation algorithm. Segmentation is followed by a merging procedure which is based on colour and boundary information of regions. The proposed algorithm has been tested on facial images, for the needs of face detection.