Mr. Zizhong Wei Profile

Zizhong Wei

SPIE Involvement:

Author

Publications (2)

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 | 11 October 2023 Paper

Image stitching method based on asphalt pavement potholes

Ronggui Ma, Mingxiao Ma, Xianglin Sun, Xunyan Huang, Zizhong Wei

Proceedings Volume 12800, 128003V (2023) https://doi.org/10.1117/12.3004300

KEYWORDS: Roads, Image processing, Image fusion, Feature extraction, Detection and tracking algorithms, Matrices, Asphalt pavements, Cameras, Feature fusion, Data modeling

Read Abstract +

An asphalt road pothole image stitching algorithm is proposed to address the issues of low feature point matching accuracy, loss of pothole disease information, ghosting and deformation of the pothole when using traditional image stitching algorithms. The goal is to stitch the images captured by the pavement image acquisition equipment to form a complete asphalt pavement picture with the disease information of the pothole area intact. The stitched image's pixel point coordinates are transformed to the coordinates of the reference image using a single-strain matrix after first extracting the pit regions in the image and extracting feature points for these regions using the MSER-SIFT feature extraction algorithm. Next, the best matching point pairs are found using an improved random sampling consistency algorithm. Finally, a region-weighted averaging approach is utilized to merge the images. The experimental asphalt road images include pavement images with sufficient light during the day, pavement images with complete pothole disease information, pavement images with incomplete potholes, and pavement pothole images at night to test the effectiveness of pavement stitching under various conditions. The research results show that this splicing method not only improves the matching accuracy and speed of the traditional splicing algorithm, but also ensures the integrity and invariance of the pavement pothole information.

Proceedings Article | 11 October 2023 Paper

Road pothole extraction method based on improved normal vector distance

Ronggui Ma, Xianglin Sun, Mingxiao Ma, Zizhong Wei, Xunyan Huang

Proceedings Volume 12800, 128004Y (2023) https://doi.org/10.1117/12.3004073

KEYWORDS: Point clouds, Roads, Feature extraction, Covariance matrices, 3D modeling, Data modeling, Asphalt pavements, 3D image reconstruction, Visualization, Contour extraction

Read Abstract +

To address the problem of low accuracy of the traditional 3D laser point cloud pavement potholes extraction algorithm, this paper proposes a road potholes extraction method based on the improved normal vector distance. Then, the normal vector distance of the sampled point is obtained by calculating the distance from the sampled point to the tangent plane of the quadratic surface of the local neighborhood, which is used to describe the 3D features of the sampled point; then, the normal vector distance is diluted and the features are extracted by the Douglas- Peucker algorithm. Finally, the Alpha-Shape algorithm is used to further fit the pit contour and remove the internal noise points, and the B-sample interpolation is used again to fit the boundary of the extracted pit contour to obtain the final pit boundary point cloud collection. The final experimental results show that the average relative error of the pit depth is 3.70%, which is 9.31% higher than that of the traditional method, the average relative error of the extracted pit area is 3.82%, which is 7.33% higher than that of the traditional method, and the average relative error of the extracted pit perimeter is 1.41%. The experimental results show that the method in this paper can extract the pavement pothole features well and improve the performance in terms of the accuracy of pothole feature description compared with the traditional method.

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