Abstract
Tamura features have been found to be effective in describing image textures and contrast is one of the Tamura features popularly used. As a global variable, contrast can well describe the statistical distribution of the brightness in the entire image, but cannot reflect the local brightness information of the image. To solve this problem, this paper proposes an improved texture feature extraction method which makes use of the statistical moments of intensity histogram to extract more information from the image. Tested on a tyre tread pattern dataset, the proposed method is found to be able to provide better retrieval performance than other existing methods.
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Liu, Y., Li, Z., Gao, ZM. (2013). An Improved Texture Feature Extraction Method for Tyre Tread Patterns. In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_89
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DOI: https://doi.org/10.1007/978-3-642-42057-3_89
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-42056-6
Online ISBN: 978-3-642-42057-3
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