{'fraction_non_alphanumeric': 0.014241486068111455, 'fraction_numerical': 0.002476780185758514, 'mean_word_length': 4.855072463768116, '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}}
Real time recognition of traffic light and their signal count-down timings

This paper describes an efficient method to detect traffic lights and recognize their corresponding signal count-down timings. Driver Assistance System (DAS) are applications installed in vehicles that provide guidance for safe driving. Traffic Light detection is also a part of the DAS. The work is split into two parts of which, the first part deals with the detection of traffic lights. The changing traffic lights are detected by extracting the candidate region of traffic light and timer display by color segmentation using thresholding. The primary traffic light is detected by comparing the count of red pixels with the count of green pixels that is obtained as a result of thresholding. The second part recognizes the LED digits in the timer display by color segmentation, which is segmented and extracted by horizontal and vertical scanning. The extracted image is then resized to a standard size which is then converted into its binary form and bounding boxes of static width is placed over each segment of the extracted LED. The on/off status of each LED segment is obtained for all the seven segments and based on the different combination of each LED segment status, the digits can be recognized. DAS provides better realization of comfort, fuel economy and safety. The proposed method is able to detect the predominant traffic light and signal timings in a reasonable time. Experimental results show that an accuracy of 96% and 88% has been achieved for detection of traffic lights and recognition of LED digits respectively.