{'fraction_non_alphanumeric': 0.018915510718789406, 'fraction_numerical': 0.0025220680958385876, 'mean_word_length': 5.015151515151516, '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}}
Comparison and implementation of motion detection methods for sperm detection and tracking

Intra Cytoplasmic Sperm Injection (ICSI) is one of in-Vitro Fertilization (IVF) method that inseminating embryos and sperms outside of human body. This procedure has very low successful rate, with average of 30%. To improve the success rate of this method, there are many approaches have been done. One of those methods is analyzing sperm morphology and its motility as an attempt to obtain the best sperm. This approach needs detecting and tracking methods to conduct grading step. In this paper we compared a few motion detection methods to detect and track human sperm. Experiment result showed that Gaussian Mixture Model with Hole Filling Algorithm obtains the highest for human sperms detection.