Plant leaf classification using color on a gravitational approach

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Abstract

Literature describes the analysis and identification of plant leaves as a difficult task. Many features may be used to describe a plant leaf. One of them is its texture, which is also one of most important features in image analysis. This paper proposes to study the texture information of all three color channels of a plant leaf by converting it into a simplified gravitational system in collapse. We also use fractal dimension to describe the states of the gravitational collapse as they occur. This enable us to describe the texture information as a function of complexity and colapsing time. During the experiments, we compare our approach to other color texture analysis methods in a plant leaves dataset. © 2013 Springer-Verlag.

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APA

Sá, J. J. D. M., Backes, A. R., & Cortez, P. C. (2013). Plant leaf classification using color on a gravitational approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8048 LNCS, pp. 258–265). https://doi.org/10.1007/978-3-642-40246-3_32

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