Automatic identification and detection system of digital vernier caliper jumps based on CNN

Shijie Gao; Jiande Su; Xiaohui Shan

doi:10.1117/12.2642614

28 July 2022 Automatic identification and detection system of digital vernier caliper jumps based on CNN

Shijie Gao, Jiande Su, Xiaohui Shan

Proceedings Volume 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022); 123031D (2022) https://doi.org/10.1117/12.2642614
Event: International Conference on Cloud Computing, Internet of Things, and Computer Applications, 2022, Luoyang, China

Abstract

In order to solve the key problem of hop count detection of digital vernier calipers before leaving the factory, and the traditional manual detection method requires high labor and is inefficient, a digital caliper based on convolutional neural network and OpenCV computer vision library is designed. Identify automatic detection systems. Firstly, according to the spatial position and size distribution characteristics of the digital display screen of the digital vernier caliper, the digital display area image of the caliper is collected by calling a drive-free USB industrial camera in opencv-python, and preprocessed, and then the convolutional neural network is used. The (CNN) model conducts data training on the image samples of the digital display area, and finally the test part conducts a digital recognition detection experiment of 20 frames per second on the digital display area. The experimental results show that the digital vernier caliper automatic identification and detection system based on the convolutional neural network model has a digital recognition accuracy rate of 99.32%, and the accuracy fluctuation is only 0.68%, which better realizes the need to log the digital vernier caliper before leaving the factory. Hop detection is performed for this purpose.

Citation Download Citation

Shijie Gao, Jiande Su, and Xiaohui Shan "Automatic identification and detection system of digital vernier caliper jumps based on CNN", Proc. SPIE 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022), 123031D (28 July 2022); https://doi.org/10.1117/12.2642614

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
4 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Convolutional neural networks

Image processing

Digital imaging

Image segmentation

System identification

Cameras

Convolution

Show All Keywords

Keywords/Phrases

Search In:

Publication Years