Abstract

Conventionally, weave repeat is identified manually by extracting individual warp or weft yarns from the fabric. This process
can be troublesome and time-consuming. Therefore, automatic methods capable of identifying woven fabric repeat can be
very useful.
This paper describes the application of a new algorithm using image processing techniques for the development of an
automatic method, capable of identifying weave repeat. This method is based on scanning and obtaining a gray scale image of
the original sample and enhancing it by morphological operations. The enhanced image is filtered by steerable vertical filters
and then segmented into blocks showing either a warp or a weft point. The blocked image is divided into specific sub images,
followed by operating sum over their columns and forming a matrix from them. A primary and secondary threshold is then
defined giving rise to the formation of the weave pattern in the form of black and white squares. To identify the weave repeat,
a matrix, replacing the black and white squares of the weave pattern by zero and one is produced. Then the first repeating
row and column are found, showing the start of the next repeat vertically and horizontally, leading to the identification of
weave repeat.
Keywords: weave repeat; image analysis; morphological operations; steerable filters; nonlinear diffusion filtering; fuzzy
c-means clustering