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: 51,142,758

 Pomelo’s Quality Classification based on Combination of Color Information and Gabor Filters
Tác giả hoặc Nhóm tác giả: Huynh Huu Hung, Nguyen Trong Nguyen, Jean Meunier
Nơi đăng: The Fifth International Conference on Knowledge and Systems Engineering (KSE 2013); Số: 1;Từ->đến trang: 389-399;Năm: 2013
Lĩnh vực: Công nghệ thông tin; Loại: Báo cáo; Thể loại: Quốc tế
TÓM TẮT
Vietnam is a country with strength in fruit trees, including many fruits well-known to the world, such as pomelo, dragon fruit, star apple, mango, durian, rambutan, longan, litchi and watermelon. However, the competitiveness and export of these fruits are low and incommensurate with the existing potential. To solve this problem, Vietnam is studying sustainable directions by investing machinery for automation process to meet international standards. In this paper, we introduce an effective method for detecting surface defects of the pomelo automatically based on the combination of color information and Gabor filter. The proposed approach has been tested with high accuracy and is promising.
ABSTRACT
Vietnam is a country with strength in fruit trees, including many fruits well-known to the world, such as pomelo, dragon fruit, star apple, mango, durian, rambutan, longan, litchi and watermelon. However, the competitiveness and export of these fruits are low and incommensurate with the existing potential. To solve this problem, Vietnam is studying sustainable directions by investing machinery for automation process to meet international standards. In this paper, we introduce an effective method for detecting surface defects of the pomelo automatically based on the combination of color information and Gabor filter. 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