{'fraction_non_alphanumeric': 0.013613861386138614, 'fraction_numerical': 0.0, 'mean_word_length': 5.472, '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}}
Various Methods for Edge Detection in Digital Image Processing

In computer and image processing edge detection playing a vital role. It is problems of fundamental importance in image analysis edge characterizes object boundaries and are useful for segmentation, registration and identification of objects in a scene. In this paper we discuss feature extraction. Firstly we apply Gaussian noise removal method for removing the noise from image collected. Secondly some edge detection operator such as Binary Morphology, canny edge detection, log edge detection, differential edge detection are applied and analyzed. According to simulated result the advantages and disadvantages of these edge detection operators are compared. It is shown that the binary morphology operator can obtain better edge detection.