Fabrication Of Patterns Research Articles

Detection method for analyzing water spots in fabrics by near-infrared hyperspectral imaging

Water spot detection in fabrics is conventionally reliant on direct visual assessment, a practice ingrained in our daily lives and textile inspection field. While valuable, this method’s accuracy can be significantly affected by factors like fabric color and patterns resulting from additive textile dyes. In response, we present a detection method employing near-infrared (NIR) hyperspectral imaging, effectively reducing the influence of textile dyes and highlighting water spots. Initially, we acquired NIR hyperspectral images of fabric samples post-dyeing and moisture content conditioning. Remarkably, we observed that typical textile dyes minimally affected the NIR reflectance within the wavelength range of 1265–1626 nm, with a discernible decrease correlated to higher fabric moisture content. Subsequently, we captured NIR hyperspectral images of nine fabrics exhibiting varied colors and water spot characteristics. These images were then transformed into grayscale representations. Among them, the NIR images at 1459 nm emerged as preferred feature images for water spot detection, determined through analyses of contrast, entropy, and principal component images. While conducting a spray-rating evaluation of water spots in water-sprayed samples, comparing them with their respective feature images; the results affirm the efficacy of our developed feature images in facilitating visual identification and analysis of water spots in diverse fabrics, ultimately enhancing the accuracy of fabric water-repellency evaluation.

Typological factors of urban development of inconvenient lands in the structure of Irkutsk riparian zones

The paper considers the main approaches to organization and development of inconvenient lands in a city structure. The aim was to develop an interdisciplinary research model and to design an urban development plan for the territories of floodplains with a high level of flooding. The main objectives of the study consisted in identification of factors for assessing the urban development capacity of territories with various degrees of flooding; determination of principles for increasing the urban development capacity of wetland areas; formation of methods for urban development of inconvenient lands, taking into account landscape planning factors of the floodplain complex organization. The paper considered the main approaches to organizing inconvenient urban areas as a whole. However, most attention was paid to the wetland areas of vast floodplains from the standpoint of geotechnical, biotechnical and urban morphological methods of organizing the territory. The methodology of territory assessment and transformation via methods of geoplastics was developed in the process, and the basic principles of sustainable landscape-planning pattern of the urban fabric under conditions of flooding were formulated. As a result, a model of territory organization was developed based on the methods of urban landscaping and building morphotypes on the example of Irkutsk.

CPO and quantitative textural analyses within sheath folds

We investigate the intra- and inter-crystalline deformation processes involved in sheath fold development combining complementary fabric analysis techniques and 3D modelling by neutron tomography. The investigated sheath fold is a multi-layered sub-metre scale single-eye structure, developed in metapsammites from the Ben Hope Nappe, overlying the Moine Thrust Zone of NW Scotland. Crystallographic Preferred Orientations (CPOs) of quartz and biotite were acquired through a Neutron Diffractometer and an SEM-EBSD system to compare the full-fabric of the main phases and the active slip systems for an “in situ” structural control. Combined with orientation maps and grain size maps, results show that, despite the different structural positions of the investigated microdomains (upper vs lower fold limbs, inner vs outer sheath closures, distance from hinge of the sheath fold), quartz and biotite deformed uniformly, suggesting a constant differential stress and orientation of the kinematic vorticity axis. Previously recognized detachment horizons within the sampled sheath fold do not affect the fabric patterns recorded by quartz and biotite. This may be interpreted in two different ways: i) detachments formed during earlier active folding and prior to passive amplification of folds associated with more uniform flow to create the sheath fold geometries; ii) the quartz c-axis patterns are coeval with a late deformation phase (loading of the orogenic wedge) that pervasively obliterated the previous fabric and therefore did not preserve the active folding component. Several pieces of evidence reported here, such as top-to-SE normal-shear sense which is opposite to the regional kinematics, are more supportive of the second hypothesis. The analysis of mineral textures provides an improved dataset for the whole sheath fold and increases our understanding of recrystallization mechanisms active in shear zones.

An artificially-intelligent cornea with tactile sensation enables sensory expansion and interaction

We demonstrate an artificially-intelligent cornea that can assume the functions of the native human cornea such as protection, tactile perception, and light refraction, and possesses sensory expansion and interactive functions. These functions are realized by an artificial corneal reflex arc that is constructed to implement mechanical and light information coding, information processing, and the regulation of transmitted light. Digitally-aligned, long and continuous zinc tin oxide (ZTO) semiconductor fabric patterns were fabricated as the active channels of the artificial synapse, which are non-toxic, heavy-metal-free, low-cost, and ensure superior comprehensive optical properties (transmittance >99.89%, haze <0.36%). Precisely-tuned crystal-phase structures of the ZTO fibers enabled reconfigurable synaptic plasticity, which is applicable to encrypted communication and associative learning. This work suggests new strategies for the tuning of synaptic plasticity and the design of visual neuroprosthetics, and has important implications for the development of neuromorphic electronics and for visual restoration.

A facile and universally applicable additive strategy for fabrication of high-quality copper patterns based on a homogeneous Ag catalyst ink

Additive strategy has beenregardedas a promising approach for fabricating electronic copper patterns, since it has predominance over traditional lithography technology (subtractive strategy) in process simplicity, material economizing, and environmental protection. At present, the key challenge for additive strategy is how to precisely fabricate high-quality copper patterns adhering tightly to substrates, by facile and universally applicable process. Here a novel additive copper patterning process is explored by adopting a homogeneous Ag-based catalyst ink. The catalyst ink can be facilely patterned and tightly attached on various substrates by different patterning techniques, without any pre- and post-treatment procedures. In the catalyst ink formula, epoxy matrix contributes high adhesiveness and fixes ink form, valen Schiff base acts as a medium anchoring Ag catalyst, ethanol serves as both reductant and diluent, and polyethylene glycol improves hydrophility. The copper coating, forming on the catalyst layer by further electroless copper deposition process, exhibits compact structure and high electrical conductivity comparable to bulk copper. Moreover, the copper coating can be partially inserted into substrate body by porous surface design for substrates, thus achieving strong adhesion and high flexibility. This research contributes to the progress of next-generation copper patterning techniques.

Bridging the Gap Between Experimental and Natural Fabrics: Modeling Ice Stream Fabric Evolution and its Comparison With Ice‐Core Data

AbstractFabrics, also known as textures or crystallographic preferred orientations, reveal information about the deformation history of the flow of polycrystalline materials, including glacial ice, olivine in the mantle, and feldspar and quartz in the crust. Ice fabrics can have an order‐of‐magnitude effect on the ease of flow in ice sheets. However, due to the choice of ice core drill site locations, the outputs of fabric models have mostly been compared to observations from the least dynamic regions of the ice sheet (ice divides). Recently, fabric data from an active ice stream have become available from ice cores drilled at the East Greenland Ice‐core Project (EGRIP). In this work, we present a novel approach that combines satellite‐derived velocity data with the fabric evolution model SpecCAF, a continuum model based on dominant dislocation creep. We directly compare model output to ice‐core observations from EGRIP, allowing us to examine the quantitative predictions of calibrated fabric models alongside those of active ice streams for the first time. As the model is calibrated against laboratory experiments, it provides a surrogate to compare the evolution of fabrics under laboratory and natural conditions. The predictions show good qualitative agreement with the observed fabric patterns and orientations, suggesting that a fabric between a girdle and horizontal maximum, orientated perpendicular to the flow direction, is the characteristic ice stream fabric. A discrepancy in fabric strength is attributed to the lower strain rates of ice sheets compared to laboratory experiments, revealing a significant strain‐rate dependence in the processes controlling fabric evolution.

Kajian Terhadap Karakter Fizikal Fakad Bangunan bagi Tipo-Morfologi Rumah Kedai Tradisional dan Baharu di Jalan Tunku Abdul Rahman, Kuala Lumpur

The urbanization process of townships resulted in increased population needs and a change in old to modern lifestyles. Infrastructure development in old urban centers around the world is also growing rapidly over time. The process of the uncontrolled development of the morphology of the old city has greatly changed the pattern of the urban fabric, especially the buildings of the shophouses, as well as changing the physical character of the building facades as well as the overall design quality of the urban landscape. The renovation of the shophouse building to a more modern construction creates a building typology that is not responsive to the urban fabric and local context. The difference in typology has influenced the importance of the physical character of an area to the quality of its design. Many researchers and figures in the field of urbanization argue that the changing typology of new buildings due to this uncontrolled phase of urban morphology leaves various adverse impacts on the urban fabric and communities within the city. This paper aims to identify and analyze the physical character of the facades of old shophouses and new shophouses that affect the row of shophouse typologies that change according to the township’s timeline. The study area is located in Jalan Tuanku Abdul Rahman where a block of buildings consisting of several shops was chosen as the study site. Empirical examination from this study determines the physical character criteria of buildings that contribute to design quality as well as documenting the effect of physical character of buildings on design quality in Jalan Tuanku Abdul Rahman. Therefore, the results of this study and findings can be used as exposure and guidance to architects and urban planners in understanding the importance of the physical character of old shophouses, especially in Malaysia.

Streamline video-based automatic fabric pattern recognition using Bayesian-optimized convolutional neural network

Examining fabric weave patterns (FWPs) is connected to image-based surface texture feature (STF) acquisition, which can be difficult due to the structural complexity of woven fabrics. Randomly capturing static images may not correlate with the entire STF of a fabric. Traditionally, FWPs analysis is conducted by human vision, which causes an intensive cognitive load. Ultimately, the human vision-based cognitive load leads to ineffective quality inspection and error-prone FWPs analysis results. Given the above challenges, this study proposes a new streamlined video-based FWPs recognition method by incorporating Bayesian-optimized convolutional neural network (Bayes Opt-CNN). Essentially, this method is capable of leveraging the spatiotemporal features of the fabric’s intricate surface structure. In this study, to validate the effectiveness of the proposed method, seven types of fabric structures were captured as streamline videos, which were then converted into sequences of image frames. Subsequently, the Bayesian optimization process was introduced to select the best hyperparameters during CNN-based supervised learning for pattern recognition. The evaluation demonstrates that the proposed method outperforms the benchmark method for identifying FWPs.

CsPbBr3 Nanocrystals as Efficient Photocatalysts for Dehydrohalogenation: Toward Environmentally Friendly Trichloroethylene Synthesis.

The demand for a benign alternative to energy-intensive industrial chemical transformations is critical. Lead halide perovskites have emerged as promising candidates due to their unique optoelectronic properties, including high absorption coefficients in the visible region, tunable band gaps, and long charge carrier-diffusion lengths. In this study, we present a model reaction to showcase the photocatalytic utility of perovskite nanocrystals (NCs). Specifically, we demonstrate the synthesis of trichloroethylene (TCEt) from 1,1,2,2-tetrachloroethane (TCE) using CsPbBr3 NCs under white light illumination. The band-edge positions of the NCs and the redox potential of TCE enable efficient electron transfer for C-Cl bond activation. Furthermore, while ensuring operational stability, CsPbBr3 NCs undergo light-controlled modification, leading to the formation of mixed-halide perovskite (CsPbBrxCl3-x) NCs during the reaction. This procedure yields a mixed-halide perovskite that maintains stability while containing the desired halide content. Additionally, the reaction produces HBr as a byproduct, serving as a self-cleaning technique to eliminate excess Br- ions from the solution. Ultimately, we achieve nearly 100% conversion of CsPbBr3 to pure CsPbCl3 NCs, with a full width at half-maximum of approximately 11.2 nm. Our clean and efficient approach to synthesizing TCEt using perovskite NCs provides interesting insights into violet light-emitting diode (LED) fabrication and color patterning. This study highlights the promising potential of perovskite materials for sustainable chemical transformations and optoelectronic applications.

Magnetic fabric and sedimentological constraints on the paleocurrent changes within the early devonian strata from the northwestern Tarim, China

The magnetic fabric technique is widely used to measure the direction of paleocurrent and paleostress due to its speediness, precision, and cheapness. However, correlating unique magnetic fabric patterns in weakly deformed rocks with hydrodynamic or tectonic regimes remains challenging. The Early Devonian sedimentary rocks in the Keziertage Formation have well-preserved sedimentary structures and were deformed by the Cenozoic non-plunging fold. This sequence offers a prime opportunity to explore the relationship between magnetic fabric evolution, paleocurrents, and weakly deformation. Furthermore, the paleocurrent characteristics of the Keziertage Formation reflect the provenance changes during the opening of the South Tianshan Ocean. Here, we report 120 sedimentary structure-based paleocurrents and 382 magnetic fabric data from the Keziertage Formation in the Kalpin area, Xinjiang. We find that: (1) During the weakly deformation stage, the minimum axis of susceptibility's imbrication direction serves as a reliable indicator for detecting paleocurrents at the coarse sandstone layer with well-developed cross-bedding; (2) While the maximum axis of susceptibility is more consistent with the tectonic stress rather than paleocurrents. Consequently, the complexity of magnetic fabric needs to be clearly verified when it is applied in the weakly deformed strata. In the northwest margin of Tarim, both the minimum susceptibility axes of magnetic fabrics and sedimentary structures indicate a shift in the paleocurrent direction, transitioning from southwest to northeast in the mid-to-upper Keziertage Formation. This indicates significant channel changes, potentially linked to a regional change in provenance due to the Early Devonian opening of the South Tianshan Ocean.

Artificial Skin with Patterned Stripes for Color Camouflage and Thermoregulation.

Chameleons are famous for their quick color changing abilities, and it is commonly assumed that they do this for camouflage. However, recent reports revealed that chameleons also change color for body temperature regulation. Inspired by the structure of the panther chameleon's skin, a stripe-patterned poly(N-isopropylacrylamide) (PNIPAM) and polyacrylamide (PAM) hydrogel film with a laminated structure is fabricated in this work; thus, both camouflage and thermoregulation can be achieved through controlling Vis and NIR light effectively. For the PNIPAM stripe, the upper layer is the native PNIPAM hydrogel and the lower layer is the carbon nanotube-composited PNIPAM hydrogel. Thus, the PNIPAM stripe is capable of reaching 28 °C at a low environmental temperature (12 °C) and a low radiation intensity (20 mW cm-2), while preventing the body temperature from rising by changing to white under a strong radiation intensity (100 mW cm-2). For the PAM stripe, the upper layer combines colloidal photonic crystals and displays a tunable structural color by stretching, and the lower layer is mixed with PNIPAM microgels for thermal regulation. Through the fabrication of multifunctional patterns, the film can achieve both dynamic structural color and thermoregulation by precisely controlling solar radiation absorption, scattering, and reflection. More importantly, in the stripe-patterned system, the shrinkage of the PNIPAM stripes can effectively trigger the elongation of the PAM stripe, which endows the structural color changing process to be self-powered completely. The performances show that the stripe-patterned film may have potential applications in intelligent coatings, especially in areas with large temperature differences during the day such as high plains.

Axó of the spider woman: Black activism in Goya Lopes’s patterned fabrics

This article delves into the remarkable work and journey of Goya Lopes, an Afro-Brazilian designer, entrepreneur and activist. It explores the intersection of fashion and art within her designs of patterned fabrics, which encompass a wide range of everyday and unique garments, household items and more. The discussion highlights pivotal moments in Lopes’s career, including her 2008 solo exhibition The African Diaspora in Brazil, her collaborative book Imagens da Diáspora (‘Images of the diaspora’) with Brazilian historian Gustavo Falcón in 2010 and her 2017 installation Sentidos Afro-Baianos (‘Afro-Bahian senses’). Through examining select fabric patterns, the article unveils their significance as integral components of Lopes’s ongoing anti-racist activism, which has spanned over five decades from the region of Bahia in northeastern Brazil. Lastly, it delves into Lopes’s unique conceptualization of her fabrics as axós, drawing on the Yoruba term for aso (‘cloth’), and highlights their role as empowering, protective and militant Afro-diasporic mantles. The article underscores how Lopes employs fashion design as a form of activism and a subtle yet potent means to propagate political ideas.

Development method of splitting the radio-reflective large-sized reflector surface into cutting patterns made of mesh with coarse cells

An important design component of space antenna reflectors is a reflecting surface. At present, metallic knitted mesh fabric is most often used as a reflective surface; it fully meets the requirements for such surfaces in terms of physical and mechanical properties. Particularly important characteristics for large-sized reflectors are low specific gravity and high light transmission coefficient, which a mesh with coarse cells provides. However, the structural features of this mesh fabric impose additional requirements on its use as a reflective surface for large-sized transformable reflectors. The article deals with a special approach to designing patterns for a reflective surface made of mesh with coarse cells. The developed pattern cutting option allows to obtain a reflective surface with the least distortion (error), in accordance formulated criteria. The authors have suggested the option of obtaining cutting patterns of metallic mesh fabric, described the advantages of the proposed option over the classical one. The cutting pattern of the parabolic surface for the offset reflector was obtained. The proposed cutting pattern option was analyzed. Furthermore, optimization was carried out, which made it possible to maintain the integrity of the cellular structure of patterns along one loop row. The compared results show that the developed cutting pattern option completely complies with the requirements and it can be used to form a reflective surface from the metallic knitted mesh with coarse cells.

Direct etching of nano/microscale patterns with both few-layer graphene and high-depth graphite structures by the raster STM electric lithography in the ambient conditions.

The development of raster STM electric lithography has enabled the etching of nano/microscale patterns on both few-layer graphene (FLG) and high-depth graphite structures on the bulk HOPG substrates under ambient conditions. This approach utilises a nanoscale probe tip as a machining tool to directly fabricate conductive sample surfaces without the need for resists or masks. Compared to conventional nano/micro machining methods, the capability of ultraaccurate fabrication of nanoscale patterns using this technique is unmatched. The resulting FLG structures exhibit ultrasmooth flat bottoms and uniformly controlled depths ranging from 0.34 to 3.0nm (less than 10 layers). This work represents a significant advancement as it demonstrates the perfect etching of FLG structures in designated nano/microscale regions using raster STM electric lithography in the constant current mode, which reaches the limitation of top-down manufacturing techniques. Additionally, raster STM electric lithography in the constant height mode can directly etch high-depth structures (up to ∼100nm). The geometric shape and number of layers of the etched graphene structures determined by either local anodic oxidation (LAO) or the electric discharge (ED) mechanism. The LAO mechanism results in less debris and smoother edges compared to the ED mechanism, which is caused by the random electrical discharge between the tip and the sample. The well-controlled raster STM electric lithography technique is believed to be a promising and facile approach for constructing nano/microscale graphene-based devices.

A mixed‐attention‐based multi‐scale autoencoder algorithm for fabric defect detection

AbstractAiming at the defects in the process of fabric production, a defect detection model of fabric based on a mixed‐attention‐based multi‐scale non‐skipping U‐shaped deep convolutional autoencoder (MADCAE) was proposed. In a traditional encoder, the convolutional layer treats each pixel equally, so the importance of different pixels cannot be reflected. It is difficult to obtain richer and more effective information. The reconstruction of the defect region and the detection of the defect region are further affected. In this article, three different scale features of input images are extracted by enlarging the receptive field with large kernel convolution blocks. A hybrid attention module is used to ensure the richness of the extracted information in terms of space and channel. Experiments show that this method can effectively reconstruct fabric parts without requiring a large number of defect marking samples. It can quickly detect and locate defective areas of fabric patterns.

Geochemical and mechanical interactions within sheet-like granite intrusion during stress-field changeover (Moldanubian Batholith; Central European Variscides)

Late-orogenic granitoids carry unique geochemical and structural evidence of post-collisional exhumation, commonly associated with decompression melting, mixing and mingling of individual magma pulses and differentiation. The Weinsberg Type Granitoids (WTG) forming the 313.6 Ma Kaplice Sheet and 322 Ma Hojná Voda Sheet (northwestern Weinsberg Composite Pluton) have geochemical signature that demonstrates the substantial role played by the partial melting of metasedimentary sequences and the magmatic fractionation of K-feldspar, plagioclase and biotite during magma ascent and emplacement. The composition of highly peraluminous WTG were partly modified by the assimilation of host metasedimentary xenoliths. The textures of the WTG are characterised by straight crystal size distribution (CSD) consistent with in-situ crystallization and crystal/melt separation, forming abundant K-feldspar phenocryst-rich domains (KPD). The KPD were formed by redistribution of K-feldspar phenocrysts (crystal accumulation) in a suspension during magma movement followed by interstitial melt extraction and escape from the highly crystallised mush. The multiple fabric pattern within the Kaplice Sheet is the result of changeover of local stress field by varying increment of regional stress conditions and buoyancy forces at the time of magma ascent and emplacement. The steeply dipping foliation (M1) reflects the magma flow with the increment of regional stress-field (ENE–WSW oriented extension). The superimposition of flat-lying foliation (M2) with abundant particle accumulations (i.e. K-feldspar phenocrysts, enclaves and host-rock xenoliths) were associated with (a) increasing buoyancy force in ascending magma above the rate of the regional stress field or (b) collapse of ascending magma after the decreasing the buoyancy force resulting in the mush moving down.

Magnetic Fabric and Paleomagnetic Analyses of the Zaghar and Tafresh Areas, Central Urumieh-Dokhtar Magmatic Arc, Iran

Magnetic fabric, paleomagnetic, and petrophysical studies were conducted on rocks in the Tafresh area of the central Urumieh-Dokhtar magmatic arc in Iran. The samples included Late Triassic dark gray sandstone, a mafic dyke, diorites, and a felsic dyke in the Zaghar region. Hydrothermal alteration in the Spid intrusion was investigated to understand the effects of alteration on magnetic fabric patterns. The AMS measurements support the theory that the Nayband Formation was constructed under a crustal extension regime. Magnetic susceptibility anisotropy in a microdioritic dyke indicates compression from the NNE-SSW, likely due to tectonic activity. AMS results from diorites in Zaghar suggest intrusions were emplaced in extensional spaces between the Tafresh and Chaghar thrust faults. The Spid intrusion’s magnetite is the primary carrier of magnetic susceptibility, but hydrothermal alteration has partly converted it into hematite, resulting in lower susceptibility and higher porosity in altered diorites. This process leads to a bimodal distribution of magnetic lineation trends. The Spid and Zaghar massifs underwent a northward tilt of about 30 degrees around an east-west axis following the Early Miocene. Post-Eocene rotations in the area are typically within ±20 degrees. This study demonstrates how magnetic properties can provide new insights into the evolution of tectono-magmatic processes and structural controls within a magmatic arc.

Fabrication of Ultra-Stable and Customized High-Temperature Speckle Patterns Using Air Plasma Spraying and Flexible Speckle Templates.

Reliable and accurate full-field deformation measurements at elevated temperatures using digital image correlation (DIC) require stable and high-contrast high-temperature speckle patterns to be prepared on the sample surface. However, conventional high-temperature speckle patterns fabricated by the existing methods possess several limitations, e.g., easily fail to preserve original pattern features due to the harsh environment and heavily dependent on the operator's experience. In this study, we propose a reliable and reproducible high-temperature speckle fabrication method based on air plasma spraying (APS) and flexible speckle templates. This method involves covering the sample surface with pre-designed speckle templates and then spraying the melted speckle powders onto the specimen surface using an air plasma spray technique to obtain customized speckle patterns. The validity of the proposed method was verified by the speckle fabrication on both planar and curved samples and heating tests with these samples. Experimental results demonstrate that the speckle patterns made by the proposed method adhere well to the sample surface, remain stable during the heating process, and exhibit excellent agreement with the reference values in terms of the thermal expansion coefficients. The proposed method provides a reliable and efficient way to create customized and stable speckle patterns for accurate high-temperature DIC measurements.

A neural-network-based machine-learning model for fabric defect detection and classification using fused global features

ABSTRACT Detecting defects and classifying them is a primary requirement for textile industries. Manual methods of defect identification and classification happens in most cases for which the accuracy could not exceed more than 70%. A real time, fast and automated system for defect detection and classification is required for textile industries. This paper addresses this challenge and explores the use of different machine-learning models for the global features such as GLCM and Tamura extracted from checked pattern fabrics. In the training phase, machine-learning models produce an accuracy of > 90% and testing with new fabric images provides a maximum accuracy of 65%. To improve the accuracy of the classification system, an artificial neural network-based machine-learning model with features fusing has been proposed. Using the proposed approach, a testing accuracy of 80% is observed, and an accuracy of 96.1% is achieved in the training phase.

Defect detection of color-patterned fabric based on DenoisingGAN

PurposeThe defect detection problem of color-patterned fabric is still a huge challenge due to the lack of manual defect labeling samples. Recently, many fabric defect detection algorithms based on feature engineering and deep learning have been proposed, but these methods have overdetection or miss-detection problems because they cannot adapt to the complex patterns of color-patterned fabrics. The purpose of this paper is to propose a defect detection framework based on unsupervised adversarial learning for image reconstruction to solve the above problems.Design/methodology/approachThe proposed framework consists of three parts: a generator, a discriminator and an image postprocessing module. The generator is able to extract the features of the image and then reconstruct the image. The discriminator can supervise the generator to repair defects in the samples to improve the quality of image reconstruction. The multidifference image postprocessing module is used to obtain the final detection results of color-patterned fabric defects.FindingsThe proposed framework is compared with state-of-the-art methods on the public dataset YDFID-1(Yarn-Dyed Fabric Image Dataset-version1). The proposed framework is also validated on several classes in the MvTec AD dataset. The experimental results of various patterns/classes on YDFID-1 and MvTecAD demonstrate the effectiveness and superiority of this method in fabric defect detection.Originality/valueIt provides an automatic defect detection solution that is convenient for engineering applications for the inspection process of the color-patterned fabric manufacturing industry. A public dataset is provided for academia.