Evaluation of real yarn Count using Image analysis methods

Measuring yarn diameter or yarn count, yarn compressibility and their effect on fabric quality is important to both the fabric designer and the textile technologist;say in a yarn structure, fibers represent the main component the other component is air pockets created by the technology forming the structure. The knowledge of the real fibers volume within the yarn allows to better estimate various textile fabrics properties. Yarn diameter is used to predict fabric structural parameters such as width, cover factor, porosity, and fabric comfort and so on.

The fig.1 given below illustrates that the Yarn structural difference between the various counts of the yarn. The Dark grey color describes the fibers compactness and the light color describes the fibers with more air pockets dueto hairiness and less twist of yarn. So we should take care of twist factor before going to this analysis. We are know that the standard TPI is equal to product of Twist multiplier and root count.

TPI = TM x Root Count

WreTM is Twist Multiplier.

Here we assume the standard TPI for above mentioned counts of cotton yarn. For analysis the rotor spun cotton single yarn is used with various image analysis methods.The surface profile of a spun yarn may be described by three basic parameters,the overall surface appearance of yarn, surface integrity, and surface irregularities.

The used yarns diameter ranges from 6s Ne to 60s Ne and they found that the actual yarn count can be predicted by using the formula shown in Table 1. The formula shown in Table 1 implies the variation of different count with different packing fraction can be analysed.

Packing Fraction:  = Vf / Vy wre Vf is Volume of fiber / Volume ofair space

There are various tools of Images analysis methods and softwares. Example we can use the day-to-day commodities for image analysis like digital camera, web camera, Scanner etc. Since there will be a difference between these which depends on what resolution it has.

Here we noted that the apparent yarn is in inverse proportion to square root of yarn count. The twist variation is proportional to the yarn count one, so they can conclude that there is a relationship between the yarn diameter variation and the twist one. In order to avoid the variation we will assume the factors of TPI and TM for different count as per the above table. So, these parameters (the Dia and the twist yarn) will be used to estimate the yarn packing fraction.

Workings procedure:

Scan the given yarn with High resolution scanner, set the DPI 600 during scanning; the selected yarn should be 30cm in length should placed over the scanned with contrast background chart, The image can be Color or Grey scale. After getting the image open it with Adobe Photoshop, convert the image mode into Index color of 2 colors. The image is looking like the fig.2.

Select the yarn portion using Magic wand tool is marked red in fig 2. After selected go to Window menu and then Measurement log, click Record Measurements. Note the value of Area in Pixels (A). Enter the value as shown in the below table in MS Excel starting from A1 Cell. Afterwards note the value arrived in D1 cell. Again enter the same in A4.The final count will show in B8 cell.

Results and discussion:

The determination of cotton yarn count is getting easy for the designers who are working with CAD systems and scanner. They dont want bother about the Beasley balance and weighing machine. In the future research we will the linear equation for multi ply and synthetic yarn with more effective fraction values. Since a difference of 2-3% is well within the margin of error. This limit can be reduced by increasing the length of the yarn, and the standardizing the Twist of yarn.