On-line textile quality control using optical Fourier transforms

Automated fabric defect detection—A review

“…Hoffer et al [71] presented an OFT to detect and identify the defects on an on-loom neural network based inspection machine. Casterllini et al [72] and Ciamberlini et al [73] recommended that OFT be installed in an on-loom machine to detect and identify defects. A regular periodic pattern would reveal a double series of peaks with horizontal and vertical locations by OFT, depending on the spatial frequencies of 2D grating corresponding to the weft and warp textures.…”

“…Wood [18] applied Fourier power spectrum to measure the coarseness of texture on plain carpet defect detection. Similarly, optical Fourier transform (OFT) methods were applied by Hoffer et al [71] for plain cotton fabric, and by Casterllini et al [72] and Ciamberlini et al [73] for cotton and wool woven fabrics, Campbell et al [74,75] for woven denim (twill) fabric. Hoffer et al [71] presented an OFT to detect and identify the defects on an on-loom neural network based inspection machine.…”

Yarn periodical errors determination using three signal processing approaches

“…Some of the main features of the operational amplifier are [30]: ultra low offset voltage (10 μV), high open-loop gain (134 dB), high common-mode rejection (140 dB), low bias current (1 nA maximum) and a bandwidth of 1 MHz. The photodiode was chosen based on its low cost, and high sensitivity for red wavelengths (for the laser source used the response is 0.39 A/W), large active measurement area (10 × 10 mm 2 ), low dark current (maximum of 50 pA), high shunt resistance (2 G ), noise equivalent power (NEP) of 3.1 × 10 −15 W/Hz 1/2 and low terminal capacitance (3000 pF).…”

“…Qin Weigang [28] as well as Jihong Liu et al [29] propose a system to detect yarn evenness online using a CCD image sensor, digital image processing and other techniques, presenting better error results than the traditional commercial equipment manufactured by Uster. C. Castellini et al [30] present a method based on the optical Fourier transform technique for online textile quality control in order to evaluate defective fabrics. Xu Guo-sheng [31] has been able to obtain a significant improvement in the detection of yarn defects using a photoelectric inspection technique to characterize the structure found in yarn images.…”

Determination of Pore Size, Porosity and Pore Size Distribution of Woven Structures by Image Analysis Techniques

“…The introduction of image analysis techniques in textile industry and engineering enhances quality through the efficient use of control [6]. Textile porosity and other related properties, such as air permeability or light transparency, have recently become the focal point of wide and intensive research activity, because of the steadily growing interest on technical textiles and composites [7].…”