Classification of defects with ensemble methods in the automated visual inspection of sewer pipes

Wu, Wei; Liu, Zheng; He, Yan

doi:10.1007/s10044-013-0355-5

Cited by 40 publications

(22 citation statements)

References 32 publications

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“…Specifically, we extracted the feature of x-ray image by contourlet transform, Tamura texture and image histogram features. We first performed contourlet transform [7] to obtain the transformation coefficient maps of x-ray image. And then we extracted the Tamura features from transformation coefficient maps [7].…”

Section: Figure 2 the Block Diagram Of Computer Vision Based X-ray Imentioning

confidence: 99%

“…We first performed contourlet transform [7] to obtain the transformation coefficient maps of x-ray image. And then we extracted the Tamura features from transformation coefficient maps [7]. Also at the same time, we extracted image histogram feature.…”

Section: Figure 2 the Block Diagram Of Computer Vision Based X-ray Imentioning

confidence: 99%

“…In addition, we proposed a method by using contourlet transform [6,7,8] and Tamura feature [9,10,11] to extract the features of x-ray image. This work not only would provide the help for illegal objects recognition system with x-ray image, but also provides a reference for the automatic identification of irregular objects.…”

Section: Introductionmentioning

confidence: 99%

“…Contourlet transform [6,7,8], which is with the properties of directionality, multiscale, and anisotropy, can effectively capture the edge information of the image comparison with wavelet transform. Thus, contourlet transform is widely used to extract the transform coefficients maps.…”

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confidence: 99%

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An X-ray Inspection System for Illegal Object Classification based on Computer Vision

Wang¹,

Yang²,

Wu³

et al. 2016

IJSIA

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Section: Figure 2 the Block Diagram Of Computer Vision Based X-ray Imentioning

confidence: 99%

Section: Figure 2 the Block Diagram Of Computer Vision Based X-ray Imentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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An X-ray Inspection System for Illegal Object Classification based on Computer Vision

Wang¹,

Yang²,

Wu³

et al. 2016

IJSIA

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“…In [104], a comprehensive study on defects classification with ensemble methods was reported. Seven classification approaches in combination with five feature extraction and three feature representation methods were investigated for processing CCTV data.…”

Section: E Image Processing For Anomaly Detectionmentioning

confidence: 99%

Computational Intelligence for Urban Infrastructure Condition Assessment: Water Transmission and Distribution Systems

Liu

Kleiner

2014

IEEE Sensors J.

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Comparative Study of Various Deep Learning Models for Structural Anomaly Detection

Mohariya,

Gade,

Mathew

2024

Lecture Notes in Electrical Engineering

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Classification of defects with ensemble methods in the automated visual inspection of sewer pipes

Cited by 40 publications

References 32 publications

An X-ray Inspection System for Illegal Object Classification based on Computer Vision

An X-ray Inspection System for Illegal Object Classification based on Computer Vision

Computational Intelligence for Urban Infrastructure Condition Assessment: Water Transmission and Distribution Systems

Comparative Study of Various Deep Learning Models for Structural Anomaly Detection

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