{'fraction_non_alphanumeric': 0.011142061281337047, 'fraction_numerical': 0.0, 'mean_word_length': 5.267441860465116, '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 Efficient Framework for Macula Exudates Detection in Fundus Eye Medical Images

This paper presents a computer-based framework for the segmentation of medical eye images. Also, the proposed framework achieves the detection of exudates in medical eye images for better diagnosis of maculopathy disease. The proposed framework begins with fuzzy image enhancement of eye images for contrast enhancement in order to enhance the objects representation of the images. After that, the segmentation process is performed to determine the optic disc and blood vessels to remove them. The next step is detecting the region of interest edges in exudates. A gradient process is also performed on the image and the histogram of gradient is evaluated. Accumulative histogram is further generated for discrimination between image with and without exudates. A threshold histogram curve is generated based on predefined images with and without exudates for classification of images in the testing phase. The simulation results prove that the proposed framework has an appreciated performance.