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DEEP LEARNING AND IMAGE PROCESSING FOR AUTOMATED CRACK DETECTION AND DEFECT MEASUREMENT IN UNDERGROUND STRUCTURES
Deep Learning Automated Crack Detection Photographic Tunnelling Surveys
2018/6/4
This work presents the combination of Deep-Learning (DL) and image processing to produce an automated cracks recognition and defect measurement tool for civil structures. The authors focus on tunnel c...
A COST-EFFECTIVE METHOD FOR CRACK DETECTION AND MEASUREMENT ON CONCRETE SURFACE
crack detection depth camera image processing stereovision
2018/3/6
Crack detection and measurement in the surface of concrete structures is currently carried out manually or through Non-Destructive Testing (NDT) such as imaging or scanning. The recent developments in...
COMPARATIVE EVALUATION OF PAVEMENT CRACK DETECTION USING KERNEL-BASED TECHNIQUES IN ASPHALT ROAD SURFACES
Mobile Mapping RGB Camera Road Crack Extraction Kernel-based Segmentation Feature Fusion
2016/7/5
With the increasing demand for the digital survey and acquisition of road pavement conditions, there is also the parallel growing need for the development of automated techniques for the analysis and ...
Crack detection at concrete construction units from photogrammetric data using image processing procedures
Photogrammetry Change detection Tracing
2015/8/20
Cracks on the surface of a concrete construction are measured and evaluated by a digital photogrammetric method. Knowing these
cracks, the behaviour of the construction, especially using textile rein...
基于小波变换和BP神经网络的蛋壳破损检测（Crack Detection in Eggs with Multi-level Wavelet Transform and BP Neural Network）
鸡蛋 破损 检测
2009/5/22
提出了一种基于多层小波变换和纹理分析的蛋壳破损检测方法。该方法对获取的鸡蛋透射图像G分量在不同水平上进行小波分解，计算和分析各水平高频细节子图像的纹理特征参数，实验确定最有效的8个特征参数作为BP网络输入，建立结构为8—20—2的BP神经网络蛋壳破损分类模型。实验表明，该方法对无破损蛋、线状破损蛋、网状破损蛋和点状破损蛋的判别正确率分别为95%、90%、95%、80%，平均识别率为90%。
Eggshell crack detection based on acoustic impulse response and supervised pattern recognition
eggshell crack detection acoustic resonance supervised pattern recognition
2014/3/7
A system based on acoustic resonance was developed for eggshell crack detection. It was achieved by the analysis of the measured frequency response of eggshell excited with a light mechanism. The resp...
Eggshell crack detection by acoustic impulse response and support vector machine
Eggshell crack detection acoustic impulse response frequency feature support vector machine
2009/3/4
This paper investigates the effect of support vector machine (SVM) for the classification of intact and cracked eggs. The four frequency features of the sound impulse resonance of an egg excited wit...