Inspection of fabric resistance to abrasion by Fourier analysis

Escofet, Jaume; Millán, Marı́a S.; Abril, Hector C.; Torrecilla, Elena

doi:10.1117/12.308923

Cited by 17 publications

(11 citation statements)

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“…The variation of overall colour or textural characteristics from surface to surface is known as the tonality problem. Any changes in the tonality, however subtle, will still become [113,151,20,37,127,18,129] 3. Joint spatial/spatial-frequency [17,52,38,59,117,144,66,62,132,128,112,152,9,63,6,89,84,119,153 [60,123,131,80,122,39,130,149] significant once the surfaces are placed together.…”

Section: Introductionmentioning

confidence: 99%

A Review of Recent Advances in Surface Defect Detection using Texture analysis Techniques

Xie

2008

ELCVIA

398

219

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In this paper, we systematically review recent advances in surface inspection using computer vision and image processing techniques, particularly those based on texture analysis methods. The aim is to review the state-of-the-art techniques for the purposes of visual inspection and decision making schemes that are able to discriminate the features extracted from normal and defective regions. This field is so vast that it is impossible to cover all the aspects of visual inspection. This paper focuses on a particular but important subset which generally treats visual surface inspection as texture analysis problems. Other topics related to visual inspection such as imaging system and data acquisition are out of the scope of this survey. The surface defects are loosely separated into two types. One is local textural irregularities which is the main concern for most visual surface inspection applications. The other is global deviation of colour and/or texture, where local pattern or texture does not exhibit abnormalities. We refer this type of defects as shade or tonality problem. The second type of defects have been largely neglected until recently, particularly when colour imaging system has been widely used in visual inspection and where chromatic consistency plays an important role in quality control. The emphasis of this survey though is still on detecting local abnormalities, given the fact that majority of the reported works are dealing with the first type of defects. The techniques used to inspect textural abnormalities are discussed in four categories, statistical approaches, structural approaches, filter based methods, and model based approaches, with a comprehensive list of references to some recent works. Due to rising demand and practice of colour texture analysis in application to visual inspection, those works that are dealing with colour texture analysis are discussed separately. It is also worth noting that processing vector-valued data has its unique challenges, which conventional surface inspection methods have often ignored or do not encounter. We also compare classification approaches with novelty detection approaches at the decision making stage. Classification approaches often require supervised training and usually provide better performance than novelty detection based approaches where training is only carried out on defect-free samples. However, novelty detection is relatively easier to adapt and is particularly desirable when training samples are incomplete.

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Section: Introductionmentioning

confidence: 99%

A Review of Recent Advances in Surface Defect Detection using Texture analysis Techniques

Xie

2008

ELCVIA

398

219

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“…Recently, the local binary pattern (LBP) was proposed and has been successfully applied to fabric defect detections, ceramic tile defect detection, and real-time inspection tasks [8][9][10][11]. In frequencydomain approaches, the Fourier transform and the Gabor transform were applied to detect defects for fabric, pattered wafer, wood, and metal surface [12][13][14][15][16][17][18][19][20][21]. Besides, the wavelet transform is commonly used to extract the texture features [22,23].…”

Section: Introductionmentioning

confidence: 99%

Defect detection of polycrystalline solar wafers using local binary mean

Rheem

2015

Int J Adv Manuf Technol

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Polycrystalline solar wafers consist of various crystals and their surfaces have heterogeneous textures. The conventional defect detection methods cannot be applied to their solar wafers. In this paper, we propose a concept of local binary mean and its optimization method for selecting optimal threshold T . The input image is broken down into a set of K patch images. Each patch image is used to calculate its local binary mean. The local binary mean value is used as the discrimination measure for detecting defects. Experimental results show that our proposed method achieves a detection rate of 91∼94 %. Compared with related defect detection methods, the proposed method has the advantage of detecting various kinds of low gray-level defects such as micro-cracks, fingerprints, and contaminations simultaneously.

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“…They have been applied to industrial inspection tasks such as wood inspection [5], carpet wear assessment [6] and roughness measurement of machined surfaces [7]. In spectral-domain approaches, texture features are popularly derived from the Fourier transform [8,9] for fabric defect detection [10,11] and patterned wafer inspection [12] in semiconductor manufacturing. Gabor transform [13][14][15] is also commonly used to design a bank of convolution filters that represent the characteristics of the textured patterns, and has been applied to the inspection of wooden surface [16], granite [17], steel surfaces [18] and textile fabrics [19].…”

Section: Introductionmentioning

confidence: 99%