A system for automated visual inspection of ceramic tiles

Desoli, G.S.; Fioravanti, Stefano; Fioravanti, R.; Corso, D. Del

doi:10.1109/iecon.1993.339359

Cited by 12 publications

(3 citation statements)

References 5 publications

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“…Patterned texture is commonly found in wallpapers [1], household ceramics [2,3] and patterned fabric [4][5][6]. As modern manufacturing processes [7] of these patterned objects are not perfect, defective patterns are frequently found on these items.…”

Section: Introductionmentioning

confidence: 99%

Motif-based defect detection for patterned fabric

Ngan

Pang

Yung

2008

Pattern Recognition

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Section: Introductionmentioning

confidence: 99%

Motif-based defect detection for patterned fabric

Ngan

Pang

Yung

2008

Pattern Recognition

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“…Another aspect of image enhancement is to make available better input for other automatic image processing operations [8]. The main goal of image enhancement is to alter one or more characteristic of captured image to make it more appropriate and reliable for a specific feature extraction.…”

Section: Image Enhancementmentioning

confidence: 99%

An Enhanced Automatic Surface and Structural Flaw Inspection and Categorization using Image Processing Both for Flat and Textured Ceramic Tiles

Islam¹,

Sahriar²

2012

IJCA

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As the price of ceramic tiles depend on its limpidness and precision of surface texture, color and shape, it's in fact a great challenge to control surface eminence and uphold production rate in the field of industrial fabrication of ceramic tiles. Under consideration these criteria, in this research paper, we have proposed an enhanced automatic surface flaw detection and categorization procedure that is able to guarantee the quality of ceramic tiles as well as production rate in industrial fabrication. Our proposed model plays an important role for automatic revealing of surface flaw during production and packaging. This proposed model includes an automatic categorization technique using computer vision that helps us to make sense about the pattern of surface defect within a very short time and also helps to make quick decision about the recovery process. Moreover, it also ensures the quality of tiles automatically during packaging procedure so that the defected tiles may not be mixed up with the fresh tiles.

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“…In particular, the detection of large defects has been extensively investigated. By contrast, the problem of detecting very small defects (e.g., cracks or scratches) on randomly textured surfaces has not received much attention [2,3]. In this paper, we address this problem and describe a new technique developed for the detection of cracks on textured images (both regular and random textures).…”

Section: Introductionmentioning

confidence: 99%

Crack detection by a measure of texture anisotropy

Bruzzone

Roli

Serpico

1995

Image Analysis and Processing

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In this paper, the problem of automatic visual inspection of textured surfaces is addressed. In particular, a technique for crack detection on both regularly and randomly textured images is presented. The technique is based on a new measure of texture anisotropy that allows an easy discrimination between defect pixels and defect-free ones. This technique was used to detect cracks on granite slabs. The reported results confirm its effectiveness

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A system for automated visual inspection of ceramic tiles

Cited by 12 publications

References 5 publications

Motif-based defect detection for patterned fabric

Motif-based defect detection for patterned fabric

An Enhanced Automatic Surface and Structural Flaw Inspection and Categorization using Image Processing Both for Flat and Textured Ceramic Tiles

Crack detection by a measure of texture anisotropy

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