Fabric defect detection using morphological filters

Mak, K. L.; Peng, Pai; Yiu, Ka Fai Cedric

doi:10.1016/j.imavis.2009.03.007

Cited by 212 publications

(104 citation statements)

References 30 publications

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“…Texture (7) Co-occurrence matrix Textile (8) Principle component analysis Wood (9) Mean shift Solar wafer (10) Weibull Synthetic aperture radar (SAR) image (11) Structural algorithm Edge detection PZT, (12) Ceramic (13) , Flash thermography (FT) (14) Morphological operation Textile, (15)(16)(17) Ceramic (18) Spectral and filtering algorithm…”

Section: Imaging Systemmentioning

confidence: 99%

A Practical Low-Cost Machine Vision Sensor System for Defect Classification on Air Bearing Surfaces

2017

Sensors and Materials

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Keywords: air bearing surface, head gimbal assembly, defect detection, machine vision, region of interestIn this paper, we present a newly adapted machine vision method and a practical low-cost machine vision sensor for defect classification of the air bearing surfaces (ABSs) of a hard disk drive, which controls the flying height of the recording heads moving above a disk in operation. A defective ABS can cause poor reading and writing performance; hence, it is necessary to verify its integrity before assembling it into the final product. The proposed sensor system was designed and implemented to detect defects by an effective combination of image segmentation and block matrix techniques as well as classifying them using an expert system under dark-and bright-field conditions. Our system processes subregions of interest and sub-blocks in parallel so that they can take advantage of multiple processor cores. From the trial runs, the small fractional error and low average processing time suggested that our proposed system is effective and can be used in an industrial assembly line.

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Section: Imaging Systemmentioning

confidence: 99%

A Practical Low-Cost Machine Vision Sensor System for Defect Classification on Air Bearing Surfaces

2017

Sensors and Materials

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“…Formula for dilation is , AB  (6) The basic effect of the operator on a binary image is to gradually enlarge the boundaries of regions of foreground pixels. Thus areas of foreground pixels grow in size while holes within those regions become smaller [20]. In dilation we increase the white pixel in the image making, it look broader.…”

Section: Dilationmentioning

confidence: 99%

“…These techniques can also be used to find specific shapes in an image [43]. The process of "opening" an image will likely smooth the edges, break narrow block connectors and remove small protrusions from a reference image [20].…”

Section: () a B A B B     (7)mentioning

confidence: 99%

Fabric Defect Detection in Textile Images Using Gabor Filter

Sajid¹

2012

IOSRJEEE

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“…The complex texture structure of fabrics has great background interference to improve the accuracy of fabric defect detection. Therefore, in fabric detection field, the intelligent fabric detectors based on image recognition and classification has been the research hotspot, attracting a large number of experts and scholars [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

A High-Precision Fusion Algorithm for Fabric Quality Inspection

Chen¹,

Wu²,

Li³

et al. 2017

dtcse

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In order to improve the accuracy of fabric texture defect detection, a combination of algorithm with Grabcut and convolutional neural network is proposed. Firstly, a segmentation algorithm based on grab-cuts is used to locate and segment the defects in fabric images accurately. Secondly, the sample images are expanded to increasing the number of the training samples. And then, the convolutional neural network is optimized to learn the features of the fabric defects more efficiently, which make it suitable for fabric defect recognition and classification. Experimental results shows that compared with other traditional algorithms, our model gets better performance with high accuracy of fabric defect detection.

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Fabric defect detection using morphological filters

Cited by 212 publications

References 30 publications

A Practical Low-Cost Machine Vision Sensor System for Defect Classification on Air Bearing Surfaces

A Practical Low-Cost Machine Vision Sensor System for Defect Classification on Air Bearing Surfaces

Fabric Defect Detection in Textile Images Using Gabor Filter

A High-Precision Fusion Algorithm for Fabric Quality Inspection

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