{'fraction_non_alphanumeric': 0.017154389505549948, 'fraction_numerical': 0.0, 'mean_word_length': 5.888888888888889, '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}}
Distributed wireless face recognition system

A face recognition system gains flexibility and cost efficiency while being integrated into a wireless network. Meanwhile, face recognition enhances the functionality and security of the wireless network. This paper proposes a distributed wireless network prototype, consisting of feature net and database net, to accomplish face identification task by optimally allocating network resources. The face recognition technique used in this paper is subspace-based modular processing with score and decision level fusion. The subspace features are selected by a step-wise statistical procedure, Modified Indifference-Zone Method, which improves efficiency and accuracy. Fusion further improves the performance from using either the whole face or modules alone. The face recognition techniques are re-engineered to be implemented on the distributed wireless network, and the simulation result shows promising improvement over centralized recognition.