Abstract
Texture change (or retention) is an important aspect of a carpet's performance in use. Objective measurement of texture change using image analysis has become a useful tool for assessing the textural quality of carpets. This paper discusses a new approach to measuring changes in carpet texture by analyzing the Fourier power spectra of the images of control (unworn) and worn carpets. Through a series of steps involving analysis of the intensity profile of a carpet image using template matching, pre-processing by high-pass filtering, and reduction to a one-dimensional spectrum by taking the rotationally averaged power spectrum of the carpet image, a feature can be extracted that represents the pile texture change. The algorithm has been tested experimentally using a range of carpet types, including those that have been difficult to measure reliably with other image analysis algorithms. The new measure agrees well with the subjective impression of tuft texture change and wear, and excellent discrimination between different levels of wear has been achieved in all cases.
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