Abstract:
The purpose of this paper is to design a fabric defect detection system using
image processing techniques. Fabric defect inspection is one of the most important processes
to discard the inferior quality fabrics during the manufacture of fabric and garment in textile
industry. Currently, in Sri Lankan textile industries the inspection process is carried out manually
by humans and therefore subjective and prone to human error. Also, there are many other
drawbacks such as tiredness, boredom and inattentiveness which cause to reduce the efficiency
of industrial process. Because of this, the process has been automated with new computer
technologies as an effective alternative to increase the quality of fabric.
In this paper, variance analysis and intensity analysis has been used as the preceding step to
identify the defects in the fabric. Because the defect-free fabric has uniformity in the structure,
the occurrence of a defect in the fabric alters the regular structure. Therefore, the fabric defects
can be predetermined by analyzing the parameters such as variance and intensity. To improve
the efficiency of the technique and to overcome the problem of detection errors, further
thresholding, noise removal, morphological operations and connected components analysis
were carried out. To verify the success of the technique, it is implemented on plain fabric samples
with different colors containing five common defect types such as hole, missed yarn, pin hole,
knitting fault, oil mark. Eventually, based on the methodologies employed in this paper, it
provides a promising stage for the development of an automated fabric defect detection system.
This fabric fault detection system was designed and implemented using high level programming
language MATLAB.
