Cuticular Scale Measurements Using Image Analysis Techniques

Abstract

A method is described for examining and measuring fiber cuticular scale patterns from optical micrographs, impressions, or SEMs. The captured images are initially manipulated using several image processing functions to clarify scale structure. Image analysis is then done using a chain-coding routine that allows a number of measurements of the scale parameters to be made quickly and accurately. Results are given for the analysis on fiber casts of four sections of different wool types and on a series of SEM photographs of Chinese cashmere and merino wool fibers.In the textile industry, there has long been the desire in certain areas, notably quality knitwear, to be able to distinguish between the various animal fibers used to produce high quality yarns. These yarns may be 100% pure wools such as merino or 100% pure cashmere, or blends of cashmere, merino, mohair, cashgora, yak, etc. Some researchers have suggested that the measurement of the evenness of fiber diameter [ 12 ], the scale height [ 15 ] , and the ratio of the cube of the scale interval to the diameter [ 10 will distinguish between certain wool/specialty fiber combinations, but others have suggested that measurements of specific individual parameters such as these are unreliable [ 5 ] .Workers at SAWTRI are trying to identify mohair and blends of mohair for the International Mohair Association [ 13 ] . They are using SEM data and measuring scale heights manually. To date, they appear to be able to detect whether or not the fiber is 100% pure mohair but cannot identify or quantify any adulterants in mohair blends. Other work such as chemical based analysis [6 ] and cortical cell. examination from TEM data [11] ] has attempted to distinguish between wool and specialty fibers without great success. At present, long laborious methods using manual measurements of properties such as scale interval, scale height, and scale angle taken from either optical micrographs or SEMs are used by an expert operator with access to a fiber knowledge base to identify these fibers. This method has not yet been successfully used to fully identify and quantify all the fibers in a blend.It would therefore be of considerable value to garment producers if there were a quicker means of characterizing fiber types and quantification of fiber types in blends. We hope this may be possible using image analysis techniques.For the purpose of this report, we analyzed four different wool fiber types using photographs of fiber casts taken from the publication by Wildman [ 14 ] . Also we took a series of photomicrographs of SEM images of white Chinese cashmere and fine merino wool samples prepared at the Scottish College of Textiles (S.C.O.T.). These were obtained by affixing the fibers to a SEM stub and sputtering with gold. Using a 5 kV accelerating voltage, the fibers were focused on the raster screen at 1000X magnification. The fibers were examined on the raster screen, and a small representative sample set for each fiber type was photographed. The photographs were then subjected to imag...

Investigation of the structure changes and properties of stretched mohair fibre

“…The speeds of dynamic friction were 30, 75, 126, 226, 553, 1030 and 1810 cm/min. The pretension is 100 mg. At each speed the coefficient of friction l, is calculated using the formula [27]:…”

“…Many factors affecting fibre friction, such as speed, input tension, lubricant viscosity, cylinder surface roughness and other parameters. Surface scales can be observed by means of scanning electron microscopy (SEM) [26][27][28][29]. Thus, friction measurement at different speeds are likely to be representative of the friction conditions for different stretching ratios keratin fibres.…”

Optical Assessment of Porosity Parameters in Transparent Woven Fabrics

“…It is a highly developed software that has existed for a few decades, it is continuously improving, and supports different kinds of measurements based on the graphical elements of the presented pictures/images. It is used in all fields of science and technology [ 6 , 8 , 12 , 15 , 26 ].…”

Application of Wavelet Transform Method for Textile Material Feature Extraction

“…A computer based classification method for animal fibre identification may use combinations of microscopy and image analysis together with statistical and feature classification techniques (Robson, 1997(Robson, , 2000Robson et al, 1989;She et al, 2002). However, it is believed that wavelet texture analysis provides a reliable fibre classification system for the discrimination between cashmere fibre and the superfine merino fibre (Zhang et al, 2010a).…”