Patricia A. Annis

Characterizing Fabric Pilling by Using Image-analysis Techniques. Part I: Pill Detection and Description

Software was developed to detect and describe pills on solid-shade fabrics after being imaged with conventional personal-computer-based hardware. Information provided by the software included: the total number, total area, and total volume of pills present; distributions of pill size, shape, orientation angle, and contrast; and the uniformity of pill spatial distribution on the fabric. Usefulness of the hardware/software tool was evaluated by: assessing the accuracy of pill detection; measuring the reproducibility of pilling measurements; visualizing the influence of abrasive motion on pilling; comparing pilling on fabrics abraded by different laboratory-abrasion testers; and evaluating the effects of the number of laboratory-abrasion cycles, fiber content, and durable-press finish on pilling.

Characterizing Fabric Pilling by Using Image-analysis Techniques. Part II: Comparison with Visual Pill Ratings

Pilling was evaluated on 122 solid-shade fabrics in two ways: by a subjective visual rating with ASTM photographic standards and by objective image analysis by using a computer-based imaging system developed specifically for pilling analysis. Pilling features evaluated by image analysis were: the total number, total area, and total volume of pills present; coefficients of variation of distributions of pill size, shape, orientation angle, and contrast; and the uniformity of pill spatial distribution on the fabric. Relationships between human-based visual ratings and objectively measured pill features were explored.

An Abrasion Machine for Evaluating Single Fiber Transfer

An abrasion machine has been developed for laboratory use based on the principle of abrading textiles at a slow rate with a small abrasive force and then evaluating abrasion damage after only minor textile structural changes have occurred. Structural change is evaluated in terms of fiber transfer, which is the release and relocation of individual fibers. The abrasion machine is described and its use is illustrated with three fabrics by evaluating the number, length, and configuration of transferred fibers. Since most textiles transfer fibers during ordinary use and care, this machine has the potential for application to a wide variety of textile problems.

Characterizing Fuzz on Fabrics Using Image Analysis

A hardware device and software based on image analysis techniques are developed to detect and describe fuzz on fabric surfaces. Thin optical slices near the surface of fabrics are imaged with a microscope objective lens and electronic camera. Sharply focused fuzz fibers are detected within each image and described in terms of fuzz density, fuzz height, and fabric-fuzz separation. The hardware device and software techniques are evaluated by visualizing fuzz detection in individual images and by assessing the reasonableness of measured fuzz parameters for fabrics with intuitively known fuzz attributes. The instru ments usefulness is explored by assessing the influence of the yarn interlacing pattern, mechanical abrasion, and a fuzz-reducing finish on fuzz.

Fiber Transfer and the Influence of Fabric Softener

This paper reports an investigation of the influence of fabric softener on fiber transfer, using a relatively new fiber transfer abrasion tester. Nine medium-weight apparel fabrics were evaluated with and without fabric softener. Fiber transfer from these fabrics was evaluated in terms of the total number of fibers transferred, as well as the number, mean length, and length distribution of transferred fibers ≥2 mm long. Conclusions were obtained regarding the direct effect of fabric softener on fiber transfer, as well as its interactive effects with fiber denier, fabric weave, knit type, and fabric thread count. In addition, conclusions were obtained regarding mechanisms of transfer from the fabrics.

Influence of Textile Structure on Single Fiber Transfer from Woven Fabrics

A machine designed to abrade fabrics using small abrasive forces and slow rates is used to induce fiber transfer from twelve woven fabrics. Single fiber transfer, the release and relocation of individual fibers, is evaluated in terms of the number and length of fibers transferred, along with the influence of several fiber, yarn, and fabric structural features on fiber transfer. Modeling procedures indicate that structural features that predict fiber transfer best are fiber denier, fiber length, and weave type. The influence of these features is complex, and analysis of variance indicates that fiber transfer is significantly affected by their interaction.

Evaluation of a robotic transfer replicator: machine parameters that affect measurements of transfer of particulates from carpet surfaces to human skin versus human skin-like surfaces

We have designed and built a robotic machine (robotic transfer replicator) to replicate the process by which various particulates are transferred from carpet surfaces to human skin. The particulates tested included bovine serum albumin, dust mites, paint dust, pesticides, and pollen. We have investigated the effect of time of transfer, applied pressure, skin-like receptor materials, particulate size, carpet composition and construction, and motion of the receptors on the percent transfer. The amount transferred was determined to be directly proportional to the amount of particulate applied to the carpet surface. The percent transfer values ranged from 0.05% to 28% for different combinations of particulates, carpet types, and method of transfer. The percent transfer was shown to be independent of receptor size or applied pressure. To explain the variations in the percent transfer, a three-zone model for particulate penetration into carpets is proposed. While the robotic transfer replicator was not capable of reproducing exactly the results from human finger transfer, it does provide a controlled and reproducible approach to the transfer process and the ability to use toxic or pathogenic materials that could not be used with human subjects.