Evaluation of Pilling by Computer Image Analysis

Konda, Atsuo; Xin, Liang; Takadera, Masayuki; Okoshi, Yutaka; Toriumi, Koichiro

doi:10.4188/transjtmsj.41.7_t113

Cited by 24 publications

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“…Konda er al. (i988) [5] used a video camera and almost tangential illumination to capture samples. and Hsi et al (1998) (4] found that a diffuse light source is much more suitable for pilling identification than collimated lighting.…”

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Objective Evaluation of Fabric Pilling Using Image Analysis Techniques

Xin

Huang

2002

Textile Research Journal

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For quality control of textiles, it is necessary to develop an objective method to evaluate fabric pilling, rather than subjective, to improve reliability and reproducibility. This paper presents a new method to extract pill features from fabric images. In this work, we apply a two-dimensional Gaussian fit theory to train a pill template using actual pill images for pill template matching, and determine a reasonable threshold for image segmentation using a histogram-fitting technique. We then extract five parameters to describe pill properties—pill number, mean area of pills. total area of pills. contrast. and density—and establish formulas to calculate objective grades with these parameters. The results show that a good correlation can be achieved between objective and subjective data.Pilling on fabrics is a well-known phenomenon, and such an unpleasant appearance can seriously compromise a fabric's acceptability. Pilling is an effect caused by wear and tear that considerably spoils the original appearance of a fabric. It begins with migration of fibers to the external parts of yarns, so that fuzz emerges on the fabric surface. Due to friction, this fuzz gets entangled, forming pills that remain suspended from the fabric by long fibers. Pills develop on a fabric surface in four stages: fuzz formation, entanglement, growth, and wearoff (Cooke, 1985) [2]. Fabric pilling is commonly tested in the laboratory by using specific machines to generate pills. These machines are usually supplied with a stan-. dard consisting of photographs of samples with different degree of pilling. Experts with long training and experience assign a degree of pilling by looking at the sample processed by the machine. However, a common drawback of these subjective methods based on estimations by experts is their inconsistency and the inaccuracy of the rating results.Great improvement can be achieved by introducing image analysis techniques, which have been widely used for characterizing and inspecting general textured materials and, in particular, textile materials [ 1. 7. 12]. Previous valuable works on pilling evaluations by digital image analysis have been reported in references 3, 4, 5, 7, 8, 9. 11. One-way of acquiring surface data from a fabric specimen is for a laser probe to measure surface height variation, as was pointed out by Ramgulam et al. [7]. Laser-scanning techniques can acquire 3D fabric depth images to avoid the difficulty of identifying pills on a patterned fabric. However, this kind of scanning process makes data acquisition much slower than camera capturing. since it needs an x -v stage to transport the sample mechanically. In this situation, a video camera. together with an effective algorithm to identify pills. is still of great research and practical value. Konda er al. (i988) [5] used a video camera and almost tangential illumination to capture samples. and Hsi et al. (1998) (4] found that a diffuse light source is much more suitable for pilling identification than collimated lighting. These groups i...

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confidence: 99%

Objective Evaluation of Fabric Pilling Using Image Analysis Techniques

Xin

Huang

2002

Textile Research Journal

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“…Previous works in pilling evaluation by digital image analysis have been reported in Ref. [6] and Ref. [7].…”

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confidence: 99%

<title>Image segmentation based on a Gaussian model applied to pilling evaluation in fabrics</title>

et al. 1997

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Wear and tear generate fluffiness and pills that remain in the web surface spoiling the appearance of a fabric. In quality control of textiles it is necessary to have an objective method to measure pilling that improves current methods based on visual estimations of the degree of pilling by experts. Image processing techniques have been already proposed for an objective measurement of the degree of pilling. In this work we optimise a method for pilling evaluation based on image analysis that we proposed recently. The method combined operations in both the frequency and the spatial domains in order to better segment pills from the textured web background. We considered a logarithmic in base two relationship between the area of pilling and the degree of pilling based on the human perception mechanisms.We have improved the method by using a Top-hat transform for obtaining background uniformity, an image segmentation based on a Gaussian model of the background, and a selective noise elimination in the binary image.

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“…Then the pilled sample is compared with standard photographs of pilled fabric samples by visual inspection to evaluate the pilling degree that usually ranges from grade 5 (no pilling) to grade 1 (very severe pilling). Because of the inconsistency and inaccuracy of rating results obtained with the visual method, more reliable and objective methods for pilling evaluation are desirable for the textile industry.Many textile scientists have made valuable contributions to objective assessments of fabric piling [1][2][3][4][5][8][9][10][11][12][13]]. All these works, however, face the common difficulty of interference with fabric pill information from fabric color and pattern, which eventually affects pill ratings.…”

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confidence: 99%

“…Many textile scientists have made valuable contributions to objective assessments of fabric piling [1][2][3][4][5][8][9][10][11][12][13]]. All these works, however, face the common difficulty of interference with fabric pill information from fabric color and pattern, which eventually affects pill ratings.…”

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Evaluating Fabric Pilling with Light-Projected Image Analysis

Chen

Huang

2004

Textile Research Journal

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An innovative method and a device for objectively evaluating fabric pilling grade based on light projection using image analysis is presented in this paper. The method can eliminate interference with pilling information from fabric color and pattern. The device for acquiring light-projected images, detecting the profile of projected images, segmenting pills appearing on converted gray images, extracting of a pill's feature index, and so on are discussed in detail. Pilling grade is assessed by a Kohonen self-organizing feature map neural network. Thirty different kind of pilled fabric samples are trained and tested, and the correlation coefficient between the objective grade and subjective grade is 0.94 for the training samples and 1 for the testing samples. The sample number with ± I grade deviation is 5, so the objective inspection accuracy is 83%.Pilling on textile fabrics is a well-known phenomenon.The development of pills on a fabric surface, in addition to spoiling the original appearance and hand, initiates garment attrition and reduces serviceability. Pilling resistance is usually tested in the textile trade by quality control, where the fabric sample is tumbled or treated with abrasive materials to simulate normal wear. Then the pilled sample is compared with standard photographs of pilled fabric samples by visual inspection to evaluate the pilling degree that usually ranges from grade 5 (no pilling) to grade 1 (very severe pilling). Because of the inconsistency and inaccuracy of rating results obtained with the visual method, more reliable and objective methods for pilling evaluation are desirable for the textile industry.Many textile scientists have made valuable contributions to objective assessments of fabric piling [1][2][3][4][5][8][9][10][11][12][13]]. All these works, however, face the common difficulty of interference with fabric pill information from fabric color and pattern, which eventually affects pill ratings. In this paper, we propose a new method of objectively assessing fabric pilling based on light-projected image analysis, which may be the way to overcome this problem. > Experimental Device for Acquiring Light-Projected Images Figure 1 shows the device we have designed and installed to acquire the projected cross-sectional images of pilled fabric samples. Samples ( 1 ) are fixed in advance on a conveyer belt (2) driven by a motor (3) and can be wrapped closely around a shaped bar (4), which is specially designed to have a triangular cross-sectional shape and to be characteristic of a large curvature in the bar edge. When-the sample arrives at the edge of the bar where a light source (5) is positioned below, sequential projected cross-sectional images of the pilled fabric samples are captured by a CCD camera (7) positioned above the bar. Those projected images are then read into the computer to be analyzed.

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Evaluation of Pilling by Computer Image Analysis

Cited by 24 publications

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Objective Evaluation of Fabric Pilling Using Image Analysis Techniques

Objective Evaluation of Fabric Pilling Using Image Analysis Techniques

<title>Image segmentation based on a Gaussian model applied to pilling evaluation in fabrics</title>

Evaluating Fabric Pilling with Light-Projected Image Analysis

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