Surface Crack Detection in Building Wall Based on Computer Vision

2014 ◽  
Vol 651-653 ◽  
pp. 524-527 ◽  
Author(s):  
Jin Zhi Fan
Keyword(s):  
Computer Vision ◽  
Surface Crack ◽  
Crack Detection ◽  
Detection Method ◽  
Detection System ◽  
Spatial Location ◽  
Accuracy Rate ◽  
Detection Technology ◽  
Building Wall ◽  
Image Pixels

the detection technology of surface crack in building wall is studied to improve the accuracy of detection. To detect surface crack in the building wall, there will be a pixel overlap or distorted in the location of image connection if using traditional detection method to make fusion process for the different pixels. due to the accuracy requirements of image pixels in surface crack detection in building wall is relatively high, resulting in too low accuracy rate of surface crack detection in building wall. In order to avoid the above problem, a detection method for surface crack in building wall based on computer vision is proposed. The crack region’s pixel in the image of building wall’s surface is calculated, and thus to provide the basis for surface crack detection in building wall. According to the theory of computer vision, the spatial location of the surface crack region in building wall is obtained. Experiments show that this detection system can improve the accuracy of detection, and achieve satisfactory results.

Design of Computer Vision and Image Processing Technology Based Car Keys Tooth Identification Detection System

2014 ◽  
Vol 1079-1080 ◽  
pp. 1061-1063 ◽  
Author(s):  
Hong Ying Li
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Detection System ◽  
Processing Technology ◽  
Direct Impact ◽  
Assembly Process ◽  
Accurate Identification ◽  
Detection Technology ◽  
Key Aspects ◽  
The Cost

This paper can be used as acar key toothed recognition and detection technology and computer vision, imageprocessing technology combined with interdisciplinary applications. Car lockassembly complicated procedures, identification and car keys tooth detection isone of the key aspects of automotive lock assembly, lock a direct impact on theefficiency of the assembly process. The system can effectively improve theexisting car key tooth detection technology to reduce the cost of car keystooth detection recognition, while also rapid and accurate identification, sothat the entire lock assembly process much more efficient.

A robust self-driven surface crack detection algorithm using local features

2020 ◽  
Vol 62 (5) ◽  
pp. 269-276 ◽  
Author(s):  
Aixi Zhu ◽  
Yiming Zhu ◽  
Nizhuan Wang ◽  
Yingying Chen
Keyword(s):  
Surface Crack ◽  
Crack Detection ◽  
Building Materials ◽  
Detection Method ◽  
Detection Algorithm ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Local Texture ◽  
Original Photograph ◽  
Sparse Features

This paper presents an effective image analysis method for visual surface crack detection, called a robust self-driven crack detection algorithm (RSCDA). Firstly, a local texture anisotropy (LTA) is estimated based on self-driven local feature statistics from the original photograph. Secondly, the LTA is used to detect candidate crack pixels. Finally, the actual crack pixels are accurately identified using two effective measurements for connected domains based on discriminative direction and relative sparse features. The results demonstrate that the RSCDA is an effective and robust surface crack detection method for building materials or textiles.

Surface Crack Detection Method for Ceramic Tile Based on Hessian Matrix Multi-Scale Filtering

2020 ◽  
Vol 57 (10) ◽  
pp. 101022
Author(s):  
周飘 Zhou Piao ◽  
李强 Li Qiang ◽  
曾曙光 Zeng Shuguang ◽  
郑胜 Zheng Sheng ◽  
肖焱山 Xiao Yanshan ◽  
...  
Keyword(s):  
Surface Crack ◽  
Ceramic Tile ◽  
Crack Detection ◽  
Detection Method ◽  
Hessian Matrix ◽  
Multi Scale

Bridge Surface Crack Detection Method under Multi-Scale and Multi-Perspective

2016 ◽  
Vol 10 (3) ◽  
pp. 119-130
Author(s):  
Tingping Zhang ◽  
Jianxi Yang ◽  
Xinyu Liang
Keyword(s):  
Surface Crack ◽  
Crack Detection ◽  
Detection Method ◽  
Multi Scale

LASER ULTRASONIC INSPECTION SYSTEM WITH A 3D SURFACE PROFILOMETRY TO DETECT SURFACE CRACKS

2008 ◽  
Vol 22 (11) ◽  
pp. 1051-1056 ◽  
Author(s):  
SEUNG-KYU PARK ◽  
SUNG-HOON BAIK ◽  
HYUNG-KI CHA ◽  
YONG-MOO CHEONG ◽  
WOON-IL KIM ◽  
...  
Keyword(s):  
Surface Crack ◽  
Crack Detection ◽  
Detection System ◽  
Ultrasonic Inspection ◽  
Analysis Data ◽  
Inspection System ◽  
Surface Cracks ◽  
Laser Ultrasonic ◽  
Surface Profilometry ◽  
3D Surface

We have developed a nondestructive surface-crack detection system by using laser ultrasound and optical 3D surface profilometry. The system can robustly acquire crack information by using the laser ultrasonic analysis data with visual surface profiling data where both data are produced by the same line-shaped pulse laser beam. By the help of the visual 3D shape data for a surface crack, this ultrasonic inspection system can provide reliable surface crack information. In this paper, the hardware configuration of the combined nondestructive laser inspection system to detect surface cracks will be described. Also, the experimental results to detect multi surface cracks by using the developed system will be presented.

Weak Signal Detection Method in a Stronger Noise Background

2014 ◽  
Vol 568-570 ◽  
pp. 260-264
Author(s):  
Jun Wang ◽  
Jian Ming Bai
Keyword(s):  
Detection Method ◽  
Detection System ◽  
Feasibility Analysis ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Error Angle ◽  
Noise Background ◽  
Photoelectric Detection ◽  
Detection Technology ◽  
Detection Principle

When we use the laser auto collimation theodolite to measure the azimuth error angle of air target, the strong noise background reduces the spot imaging quality and seriously influences the measuring angle ability of the theodolite. In order to solve the problem, a photoelectric detection system used to detect the weak signal is designed based the correlation detection principle and the principle of correlation detection technology is introduced. We use Simulink software presenting a simulation to the detection system and do a feasibility analysis. Finally, it’s proved that the photoelectric detection system could suppress the strong noise background, improve the SNR greatly and detect the weak signal effectively.

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