Automated, objective, and reliable fabric evaluation methods are needed as alternatives to existing visual inspection methods. A new profilometer has been developed for assessing fabric smoothness appearance by using laser triangulation and image processing techniques. The profilometer consists of a laser line projector, CCD camera, rotating stage, computer, and special software. This paper reports the basic principle of laser triangulation, image processing techniques for extracting surface profiles, wrinkle characterization methods, and the results of a trial test. The profilometer can generate results that are consistent with human observers, and the patterns and colors of the fabric do not affect the measurements. In addition, the profilometer is essentially insensitive to patterns of wrinkle orientations. This new evaluation method also solves a problem encountered in research on other instrumental evaluation techniques—the ability to discriminate differences in fabrics whose smoothness appearance falls between AATCC Test Method 124 replicas SA-3 and SA-3.5.One of the factors that influences the quality of garments is the ability of fabrics to recover from induced wrinkles or to retain a smooth appearance after repeated home laundering. Since the 1950s, many methods of assessing this property have been devised, one of the most wid y used in U.S. being AATCC Test Method 12 ] . This method allows fabrics to wrinkle by follo ing standardized washing and drying procedmtuand then compares the fabric specimens with a set of six three-dimensional replica plates. Expert observers assign a rating or grade to the specimen whose smoothness appearance most . closely matches the wrinkling characteristics of a ' photograph or replica.... There have. been attempts to automate this charac-. terization process using computers and imaging tech-' nology [ 2,4,8 ] . Computers acquire information from the specimens, compare the data with those obtained from the standard replicas, and produce ratings that are consistent with human graders. One way of acquiring surface data from a fabric specimen is for a laser probe to measure surface height variation [ 2 ] ; these devices have excellent resolution in the order of microns. Because a laser makes one measurement at a time, a mechanical stage has to be used to scan the sample in the X-and Y directions to obtain a surface map. However, this kind of scanning process makes data acquisition too slow to be suitable for industrial applications.Another method uses a video camera with a lighting system [8). These systems produce good resolution, but are sensitive to fabric color, i.e., true wrinkling on darker colors is difficult to determine. Further, the system cannot analyze fabrics with constructed or printed designs. Moire imaging has been used to acquire fabric surface data; it is efficient and effective for characterizing wrinkling of certain fabric types, but its application is also limited by its ability to rate only fabrics without patterns or designs [ 4 ] .In the research ...
In fringe projection profilometry, inevitable distortion of optical lenses decreases phase accuracy and decreases the quality of 3D point clouds. For camera lens distortion, existing compensation methods include real time look-up tables derived from the related parameters of camera calibration. However, for projector lens distortion, so far, post-undistortion methods iteratively correcting lens distortion are relatively time-consuming while, despite avoiding iteration, pre-distortion methods are not suitable for binary fringe patterns. In this paper, we aim to achieve real-time phase correction for the projector by means of a scale-offset model that characterizes projector distortion by four correction parameters within a small-enough area, and thus we can speed up the post-undistortion by looking up tables. Experiments show that the proposed method can suppress the distortion error by a factor of 20 ×, i.e., the error of root mean square is less than 45 µm/0.7‰, while also proposed improving the computation speed by a factor of 50× over traditional iterative post-undistortion.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.