{'fraction_non_alphanumeric': 0.014304291287386216, 'fraction_numerical': 0.0, 'mean_word_length': 5.311475409836065, '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}}
Genetic based Fuzzy Seeded Region Growing Segmentation for diabetic retinopathy images

Segmentation is an important task for image analysis. Region based segmentation methods are best suited for images taken in noisy environment. Selecting a seed pixel is a challenging task in region growing methods. To overcome this drawback, Genetic based Fuzzy Seeded Region Growing Segmentation (GFSRGS) algorithm is proposed in this paper. The proposed algorithm optimizes the selection of multiple seed pixels using genetic based fuzzy approach. It is experimented with diabetic retinopathy images to find out the exudates regions. The results of the proposed algorithm are compared with the ground truth data. It achieves better accuracy when compared to the existing methods.