The application of directional wavelets in multiscale representation of pulp fibre image

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Abstract

This paper proposes a novel algorithm to decompose fibre image and extract its edge characteristics. Because the characteristics of the paper fibre such as length and width play an important role in papermaking industry, so how to measure its related characteristics is important to improve the paper quality and production. An online fibre analyzer is designed based on the computer vision theory, and the distribution structure of the online fibers on image presents the multi-directional properties, so the multi-direction and multi-scale algorithm is proposed, and the directional wavelet transform is applied to the analysis of fibre image. Our analysis shows that directional wavelet transform can better reflect the edge information of images, because direction and texture information of fibre image can be better expressed. The experiment proves that the directional characterizations of fibre image can be extracted effectively.

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Hou, B. P., & Zhu, W. (2004). The application of directional wavelets in multiscale representation of pulp fibre image. In Proceedings of 2004 International Conference on Machine Learning and Cybernetics (Vol. 7, pp. 4314–4318). https://doi.org/10.1109/icmlc.2004.1384595

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