{'fraction_non_alphanumeric': 0.011131725417439703, 'fraction_numerical': 0.0, 'mean_word_length': 4.806451612903226, '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}}
Detection of multioriented texts in natural scene images

Detecting texts of multiorientation has been studied for long, yet it remains a challenging task because of the complex background and diversity of texts. For the results to be accurate, it will make use of a classification scheme using random forest classifier. Text detection becomes more challenging if the input image is a blurred one. So we make use of a blind image deblurring method for image deblurring and thus text can be detected more effectively in the deblurred image.