Twin-illumination and Subtraction Technique for Detection of Concave and Convex Defects on Steel Pipes in Hot Condition

Ono, H.; Ogawa, Akihiro; Yamasaki, Takahiro; Koshihara, Takahiro; Kodama, Toshifumi; Iizuka, Yukinori; Oshige, Takahiko

doi:10.2355/isijinternational.isijint-2018-742

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…The spot defects and steel-pit defects are determined through an active contour model to establish the surface quality. Moreover, a twin-illumination method has been performed to recognize metallic convex surfaces via harmless signals [4]. Two images are acquired from the same position but illuminated from the opposite direction to determine concave and convex surfaces.…”

Section: Introductionmentioning

confidence: 99%

Micro-Scale Surface Recognition via Microscope System Based on Hu Moments Pattern and Micro Laser Line Projection

Rodríguez

2023

Metals

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The surface engineering of metals develops high technology to detect microscale convex, concave and flat surface patterns. It is because the manufacturing industry requires technologies to recognize microscale surface features. Thus, it is necessary to develop microscopic vision technology to recognize microscale concave, convex and flat surfaces. This study addresses microscale concave, convex and flat surface recognition via Hu moments’ patterns based on micro-laser line contouring. In this recognition, a Hu moments’ pattern is generated from a Bezier model to characterize the surface recovered through microscopic scanning. The Bezier model is accomplished by employing a genetic algorithm and surface coordinates. Thus, the flat, convex and concave surfaces are recognized based on the Hu moments’ pattern of each one. The microscope system projects a 40 μm laser line on the object and a camera acquires the object’s contour reflection to retrieve topographic coordinates. The proposed technique enhances the microscale convex, concave, flat, and surface recognition, which is performed via optical microscope systems. The contribution of microscopic shape recognition based on the Hu moments’ pattern and microscopic laser line is elucidated by a discussion based on the microscopic shape recognition performed through the optical microscopic image processing.

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Section: Introductionmentioning

confidence: 99%

Micro-Scale Surface Recognition via Microscope System Based on Hu Moments Pattern and Micro Laser Line Projection

Rodríguez

2023

Metals

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Online micro defects detection for ductile cast iron pipes based on twin light photometric stereo

Wang,

Xu,

et al. 2023

Case Studies in Construction Materials

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Detection of Scratch Defects on Metal Surfaces Based on MSDD-UNet

Liu,

Qin,

Lin

et al. 2024

Electronics

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In this work, we enhanced the U-shaped network and proposed a method for detecting scratches on metal surfaces based on the Metal Surface Defect Detection U-Net (MSDD-UNet). Initially, we integrated a downsampling approach using a Space-To-Depth module and a lightweight channel attention module to address the loss of contextual information in feature maps that results from multiple convolution and pooling operations. Building on this, we developed an improved attention module that utilizes image frequency decomposition and cross-channel self-attention mechanisms, as well as the strengths of convolutional encoders and self-attention blocks. Additionally, this attention module was integrated into the skip connections between the encoder and decoder. The purpose was to capture dense contextual information, highlight small and fine target areas, and assist in localizing micro and fine scratch defects. In response to the severe foreground–background class imbalance in scratch images, a hybrid loss function combining focal loss and Dice loss was put forward to train the model for precise scratch segmentation. Finally, experiments were conducted on two surface defect datasets. The results reveal that our proposed method is more advantageous than other state-of-the-art scratch segmentation methods.

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Twin-illumination and Subtraction Technique for Detection of Concave and Convex Defects on Steel Pipes in Hot Condition

Cited by 3 publications

References 2 publications

Micro-Scale Surface Recognition via Microscope System Based on Hu Moments Pattern and Micro Laser Line Projection

Micro-Scale Surface Recognition via Microscope System Based on Hu Moments Pattern and Micro Laser Line Projection

Online micro defects detection for ductile cast iron pipes based on twin light photometric stereo

Detection of Scratch Defects on Metal Surfaces Based on MSDD-UNet

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