Mr. Kan Wang Profile

Kan Wang

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 9 September 2021 Paper

A new method to reduce the false detection rate of ceramic tile surface defects online inspection system

Kan Wang, Zeren Li

Proceedings Volume 11909, 1190903 (2021) https://doi.org/10.1117/12.2603821

KEYWORDS: Ceramics, Defect detection, Feature extraction, Detection and tracking algorithms, Convolutional neural networks

Read Abstract +

The application of intelligent inspection to the online inspection of ceramic tile surface defects not only ensures the stability of product quality but also reduces the cost of labor for enterprises. Existing detection methods often achieve good results for the detection of defects in known background textures, however, its false detection rate increases dramatically, and its practicality is greatly reduced when there are unknown background textures or defects with similar characteristics to known background textures. This paper proposes a non-defective and defective samples synchronous comparison detection(N-DSCD) algorithm which combines traditional detection with deep convolutional neural network(DCNN). Firstly, a reference image library of non-defective ceramic tiles which contains all random backgrounds of the same batch of tiles is constructed based on DCNN extracting image features in real-time. After that, a reference image with the most similar features to the image to be detected is searched out from the image library relying on the feature comparison method. Next, we feed the image to be detected and the reference image to the defect detector at the same time, the difference in results is used as the basis of judging whether the ceramic tile has defects or not. Tested on a total of 12,000 images of ceramic tiles with 20 different textures found that: the computational time of a single ceramic tile increased by only 120 ms, and the average false detection rate of 20 unknown background texture tiles was reduced from 23.1% to 5.8%. It greatly improves the practicality of the ceramic tile surface defects online inspection system and has wider economic benefits.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

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:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years