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 APPLYING COMPUTER VISION FOR INSPECTING QUALITY OF BOTTLE AND FOREIGN OBJECT DETECTION
Tác giả hoặc Nhóm tác giả: Dang Hieu Trương - Kim Anh Nguyen - Thi Thanh Van Phan
Nơi đăng: 2022 7th National Scientific Conference on Applying New Technology in Green Buildings (ATiGB); Số: ISBN 978-604-80-7240-7;Từ->đến trang: 34 - 40;Năm: 2022
Lĩnh vực: Kỹ thuật; Loại: Bài báo khoa học; Thể loại: Trong nước
TÓM TẮT
For manufacturers as well as consumers, a product with a defective bottle or the existence of foreign objects is unacceptable. This article refers to the application of computer vision as a field of artificial intelligence to the automatic of foreign object detection and the quality of bottle. The inspection is carried out at all areas including body, mouth and bottom of the bottle. For experiment of this research, the python programming language is incorporated with an open source library (OpenCV). The training of system must be ensured that computer vision works so that it is closest to human vision which means building on simulating how the human brain works, known as neural network. Input data after going through the preprocessing process will be measured and diagnosed by the computer based on the trained knowledge, thereby determining the quality of the current product. The results obtained will be shown on a Graphical User Interface to facilitate the extraction and operation.
ABSTRACT
For manufacturers as well as consumers, a product with a defective bottle or the existence of foreign objects is unacceptable. This article refers to the application of computer vision as a field of artificial intelligence to the automatic of foreign object detection and the quality of bottle. The inspection is carried out at all areas including body, mouth and bottom of the bottle. For experiment of this research, the python programming language is incorporated with an open source library (OpenCV). The training of system must be ensured that computer vision works so that it is closest to human vision which means building on simulating how the human brain works, known as neural network. Input data after going through the preprocessing process will be measured and diagnosed by the computer based on the trained knowledge, thereby determining the quality of the current product. The results obtained will be shown on a Graphical User Interface to facilitate the extraction and operation.
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