{'fraction_non_alphanumeric': 0.009146341463414634, 'fraction_numerical': 0.0, 'mean_word_length': 5.140186915887851, '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}}
Counting Cars in Traffic Using Cascade Haar with KLP

Detection of vehicles in images represents an important step towards achieving automated roadway monitoring capabilities. The challenge lies in being able to reliably and quickly detect multiple small objects of interest against a cluttered background which usually consists of road signs, trees and buildings. To this end we present a Proof of Concept Traffic monitoring application. The application counts the number of cars passing in either direction. Car detection is done using a boosted cascade of Haar features and is combined with the pyramidal KLT tracker to achieve a fast monitoring system.