Automatic Weave Repeat Identification using Image Analysis
Fatemeh Ajallouian, Hossein Tavanai, Maziar Palhang
Abstract
This paper describes the application of a new algorithm using image processing techniques for the development of a universal and almost automatic method, capable of identifying weave repeat. This method is based on scanning and obtaining a gray scale image of the original sample which is enhanced by morphological operations and then filtered by steerable vertical filters and next segmented into blocks showing either a warp or a weft point. The blocked image is divided into specific subimages, 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
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