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Vol. 32, No. 8(2), S&M2292

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Sensors and Materials
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Sensors and Materials, Volume 33, Number 2(3) (2021)
Copyright(C) MYU K.K.
pp. 789-804
S&M2495 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2021.3047
Published: February 26, 2021

Adaptive Method to Locate Seed Points Based on Information Entropy and Quadtree [PDF]

Xiaofu Du, Huilin Liu, and Hsien-Wei Tseng

(Received July 20, 2020; Accepted January 21, 2021)

Keywords: vector field visualization, streamline, entropy gradient field, quadtree

Streamlines in a signal field are analyzed to describe the changes in the signal distribution of wireless sensors in this study. To generate streamlines effectively and efficiently with seed points in a vector field, we combine several algorithms to propose an adaptive method. The method is based on a quadtree data structure and information entropy. First, we improve the speed of calculating the entropy field in a vector field by an order of magnitude using a fast entropy field calculation algorithm. In the entropy gradient field, seed points are deployed along the direction of the gradient at a certain interval from the existing seed points using an entropy gradient field seeding algorithm. Then, a quadtree grid in the entropy field is obtained by dividing the field into multiple levels with high entropy using the quadtree entropy field segmentation algorithm. Upon doing this, all nodes of the grid become seed points. These algorithms significantly improve the efficiency of seed point deployment, with different densities in different locations. As a result, a better layout of streamlines in the vector field is generated.

Corresponding author: Huilin Liu, and Hsien-Wei Tseng


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Cite this article
Xiaofu Du, Huilin Liu, and Hsien-Wei Tseng, Adaptive Method to Locate Seed Points Based on Information Entropy and Quadtree, Sens. Mater., Vol. 33, No. 2, 2021, p. 789-804.



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