{'fraction_non_alphanumeric': 0.018867924528301886, 'fraction_numerical': 0.0, 'mean_word_length': 5.21875, '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}}
Classification of Convective and Stratiform Cells in Meteorological Radar Images Using SVM Based on a Textural Analysis

This contribution deals with the discrimination between stratiform and convective cells in meteorological radar images. This study is based on a textural analysis of the latter and their classification using a support vector machine(SVM). First, we apply different textural parameters such as energy, entropy, inertia, and local homogeneity. Through this experience, we identify the different textural features of both the stratiform and convective cells. Then, we use an SVM to find the best discriminating parameter between the two types of clouds. The main goal of this work is to better apply the Palmer and Marshall Z-R relations specific to each type of precipitation.