{"title":"基于相似形状搜索视障人士的交通灯检测","authors":"Jie Ying, Jinzhang Tian, Lei Lei","doi":"10.1109/ICICIP.2015.7388200","DOIUrl":null,"url":null,"abstract":"A new method of circular traffic light detection and recognition was proposed for the visually impaired person to help them cross the road. Similar circular and rectangular shapes detection combined with the intensity analysis was used to locate the candidate traffic lights. And traffic light color recognition was realized using color distributions of the light area in HSI color space and shape features of the lamp. Voice prompt was given after analyzing the recognition results of video sequences. Experimental results showed that the traffic light detection and recognition method has high recognition rate of 98%, and the frame processing speed was 0.09s, which met the real-time requirements.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Traffic light detection based on similar shapes searching for visually impaired person\",\"authors\":\"Jie Ying, Jinzhang Tian, Lei Lei\",\"doi\":\"10.1109/ICICIP.2015.7388200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new method of circular traffic light detection and recognition was proposed for the visually impaired person to help them cross the road. Similar circular and rectangular shapes detection combined with the intensity analysis was used to locate the candidate traffic lights. And traffic light color recognition was realized using color distributions of the light area in HSI color space and shape features of the lamp. Voice prompt was given after analyzing the recognition results of video sequences. Experimental results showed that the traffic light detection and recognition method has high recognition rate of 98%, and the frame processing speed was 0.09s, which met the real-time requirements.\",\"PeriodicalId\":265426,\"journal\":{\"name\":\"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICIP.2015.7388200\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP.2015.7388200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Traffic light detection based on similar shapes searching for visually impaired person
A new method of circular traffic light detection and recognition was proposed for the visually impaired person to help them cross the road. Similar circular and rectangular shapes detection combined with the intensity analysis was used to locate the candidate traffic lights. And traffic light color recognition was realized using color distributions of the light area in HSI color space and shape features of the lamp. Voice prompt was given after analyzing the recognition results of video sequences. Experimental results showed that the traffic light detection and recognition method has high recognition rate of 98%, and the frame processing speed was 0.09s, which met the real-time requirements.
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