The existing standard test method assesses draped fabrics two-dimensionally. In this study, a novel method is introduced to analyze and quantify fabric drapes in 3-D by using shadow moire method. Six different woven fabrics with dissimilar drape behaviors have been analyzed. A drape index has been mathematically derived from the moire patterns employing the shadow moire topography technique. The results have been compared with the standard drape coefficient. The 3-D profile of fabrics has been graphically formed and displayed applying the moire fringes’ data.

Shadow Moiré aided 3-D reconstruction of fabric drape

Detection of bone fragments and other physical contaminations in deboned poultry meat has become increasingly important to ensure food quality and safety. Traditional X-ray imaging detection technologies have significant difficulties detecting contaminations because of the meat tissue thickness variation. In order to address the thickness variation problem, in this study, a novel vision system with combined X-ray and laser 3D imaging technology has been developed for accurate physical contamination detection. The X-ray part of the combined system captures high resolution X-ray images in real-time, and the laser 3D part provides an accurate thickness profile for each piece of meat. In the combined system, the 3D ii thickness information is used to cancel the thickness variation in the X-ray image, thus the process of physical contamination detection is significantly simplified. The combined vision system is capable of detecting calcified bones (rib bones and pulley bones) at a 95% detection rate, and partially calcified bones (fan bones) at a 90% detection rate. In order to handle the inspection tasks in real-time, a multithread architecture is used in this vision system. Various threads work simultaneously in the system, synchronized with each other, taking full advantage of system resources. It is shown that real-time capability is achieved due to the multithread framework. The result of this study has the potential to promote food safety and quality by providing advanced and automated detection techniques to the poultry and food industries.

Detection of physical hazards in boneless poultry product using combined x-ray and laser range imaging technologies

The invention provides a fabric density measurement method. In the whole process of a density measuring method in the prior art, the spirit of an inspector needs to be highly concentrated, once counting errors happen, the inspector needs to start from the beginning, labor intensity of the inspector is large, the consumed time is long, efficiency is low, and fabric needs to be damaged. The fabric density measurement method comprises steps 1) after acquiring a fabric image, and preprocessing the image; 2) smoothing the preprocessed image to obtain a warp and weft distribution image; 3) copying the warp and weft distribution image, rotating a gradient angle to cover an original image to form an interference fringe image, and respectively storing the interference fringe image; (4) processing the interference fringe image to obtain a binary image, and (5) smoothing the binary image, calculating an interval between interference fringes, storing the interference fringes into a calculation unit corresponding to rotation angles respectively, calculating the longitude and latitude density of the fabric, and detecting the longitude and latitude density of the fabric through scanning image Moire interference processing of the fabric.

Fabric density measuring method

Yarn density, or yarn count, in a woven fabric is an important parameter that influences fabric structure and properties. The measurement of yarn density often involves tedious, inaccurate procedures. This paper presents a new method developed for rapid and accurate measurement of yarn density. The method takes advantage of the structural features of a woven fabric, and uses a computer-generated grating (a reference pattern) to produce digital moire interference on the fabric. The moire image is then demodulated and processed with a phase-shifting technique so that moire fringes can be extracted and counted. From the relation between the pitches of the grating and the moire fringes, the yarn density can be calculated. This technique does not need complicated optical setting or an interferometer to form moire fringes with fabrics, permitting fast and accurate measurement of yarn densities.

Ning Jiang

Papers

Measurement of yarn densities in fabrics using phase-shifted digital moire´