title: ÐÐ¸Ð´ÐµÐ¾-ÑÐ¸ÑÑÐµÐ¼Ð° ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð´Ð¾ÑÐ¾Ð¶Ð½ÑÑ Ð·Ð½Ð°ÐºÐ¾Ð² Ð´Ð»Ñ Ð¿Ð¾Ð´Ð´ÐµÑÐ¶ÐºÐ¸ Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Driver Assistant: Traffic Sign Recognition based on Vision System
Creators: name: Ð¯ÑÑÐµÑ Ð¥Ð°ÑÑÑÑ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2018
Subjects: ÐÐ½Ð°Ð»Ð¸Ð·Ð°ÑÐ¾ÑÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
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description: Ð Ð½Ð°ÑÑÐ¾ÑÑÐµÐ¹ ÑÐ°Ð±Ð¾ÑÐµ Ð¿ÑÐ¸Ð²ÐµÐ´ÐµÐ½Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð´Ð¾ÑÐ¾Ð¶Ð½ÑÑ Ð·Ð½Ð°ÐºÐ¾Ð², Ð¿ÑÐµÐ´Ð½Ð°Ð·Ð½Ð°ÑÐµÐ½Ð½Ð¾Ð¹ Ð´Ð»Ñ Ð¿ÑÐµÐ´Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð²Ð¾Ð´Ð¸ÑÐµÐ»Ñ Ð´Ð¾Ð¿Ð¾Ð»Ð½Ð¸ÑÐµÐ»ÑÐ½Ð¾Ð¹ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¸ Ð¸ Ð¿Ð¾Ð´Ð´ÐµÑÐ¶ÐºÐ¸ Ð¿ÑÐ¸Ð½ÑÑÐ¸Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð¿Ð¾ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð°Ð²ÑÐ¾Ð¼Ð¾Ð±Ð¸Ð»ÐµÐ¼. ÐÐ»Ð³Ð¾ÑÐ¸ÑÐ¼ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ ÑÐ¾ÑÑÐ¾Ð¸Ñ Ð¸Ð· ÑÑÐµÑ Ð¾ÑÐ½Ð¾Ð²Ð½ÑÑ ÑÑÐ°Ð¿Ð¾Ð²: ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ Ð¿Ð¾ ÑÐ²ÐµÑÑ, Ð¿Ð¾Ð¸ÑÐºÐ° Ð´Ð¾ÑÐ¾Ð¶Ð½ÑÑ Ð·Ð½Ð°ÐºÐ¾Ð² Ð¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸.
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description: This thesis presents a traffic sign recognition system and classifies road and traffic signs for purpose of help the driver to take his action correctly based on the traffic sign which detected by the system. It uses images taken by a camera on vehicle moving on the road. The system is consisting of three main stages, color segmentation, recognition and classification.
At the first the color segmentation algorithm has been developed and tested. The input is a RGB image color and the output of the segmentation is a binary image has the road traffic signs as well as number of objects with the same colors. This algorithm has been using hundreds of images and the algorithm is performing well. It also robust as it was tested on different signs in different places with different weather and in different times of the day. Approximately 85% successful segmentation rate was achieved by using this algorithm.