{'fraction_non_alphanumeric': 0.008888888888888889, 'fraction_numerical': 0.0, 'mean_word_length': 5.087837837837838, '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}}
Gender Based Access Control System

Gender classification finds out whether the given facial image belongs to male or female. Face detection is feature based approach, the apparent property of the face such as skin color and face geometry are used. Feature based face detection method depends on feature derivation and analysis to gain the required knowledge about face. This recognized gender through classification can be used to give the authorized access at some public spaces or some specific places where particular gender people are expected to come and have access. The system is developed using simple edge computing device Raspberry pi interfaced with camera and solenoid latch. The openCV and python based Artificial Neural Network model is used to classify the gender. This paper discuss the need and implementation of such system with its parametric case study for future implementation.