Thông tin chung

  English

  Đề tài NC khoa học
  Bài báo, báo cáo khoa học
  Hướng dẫn Sau đại học
  Sách và giáo trình
  Các học phần và môn giảng dạy
  Giải thưởng khoa học, Phát minh, sáng chế
  Khen thưởng
  Thông tin khác

  Tài liệu tham khảo

  Hiệu chỉnh

 
Số người truy cập: 51,285,225

 Traffic Sign Recognition using Gabor Filters and Artificial Neural Network
Tác giả hoặc Nhóm tác giả: Huynh Huu Hung, Nguyen Trong Nguyen, Jean Meunier
Nơi đăng: The 10th IEEE RIVF International Conference on Computing and Communication Technologies (RIVF-2013); Số: 1;Từ->đến trang: 177-200;Năm: 2013
Lĩnh vực: Công nghệ thông tin; Loại: Báo cáo; Thể loại: Quốc tế
TÓM TẮT
Driver error is the most common cause of traffic accidents. So now there are many studies about automatic driving system, to assist the driver, to reduce the risk of an accident. One of the main tasks of these researches is traffic sign identification. This paper proposes a new approach of traffic sign recognition using the combination of Gabor filters and an artificial neural network, and the application of it on intelligent cars which can recognize the traffic signs and take a decision according to the signs it reads. Traffic signs are detected base on the color information. Then detected signs are classified using correlation with standard sign shapes. The recognition step uses an artificial neural network composed Gabor filters with different parameters. The proposed approach has been tested with high accuracy and is promising.
ABSTRACT
Driver error is the most common cause of traffic accidents. So now there are many studies about automatic driving system, to assist the driver, to reduce the risk of an accident. One of the main tasks of these researches is traffic sign identification. This paper proposes a new approach of traffic sign recognition using the combination of Gabor filters and an artificial neural network, and the application of it on intelligent cars which can recognize the traffic signs and take a decision according to the signs it reads. Traffic signs are detected base on the color information. Then detected signs are classified using correlation with standard sign shapes. The recognition step uses an artificial neural network composed Gabor filters with different parameters. The proposed approach has been tested with high accuracy and is promising.
© Đại học Đà Nẵng
 
 
Địa chỉ: 41 Lê Duẩn Thành phố Đà Nẵng
Điện thoại: (84) 0236 3822 041 ; Email: dhdn@ac.udn.vn