China
Africa
Explore chapters and articles related to this topic
Algorithms for Drawing Graphics Primitives on a Honeycomb Model-Inspired Grid
Published in D. P. Acharjya, V. Santhi, Bio-Inspired Computing for Image and Video Processing, 2018
Almansa [1] presents a quantitative means to measure the elective resolution of image acquisition systems, one that can be used as a basis of comparison of square and hexagonal sampling as well as for improving image resolution. Wu [46] presented a hexagonal discrete cosine transform (HDCT) for encoding the hexagonally sampled signals. He concluded that hexagonal sampling is the optimal sampling strategy for two-dimensional signals in the sense that exact reconstruction of the waveform requires a lower sampling density than those with alternative schemes. An efficient 3D line generation algorithm on a hexagonal prism grid is proposed by [8]. The algorithm is based on the adjunct parallelopiped grid and the 3D cubic Bresenham’s line drawing algorithm. The algorithm can be implemented using only integer arithmetic operations. So, it is faster, and the accumulation of rounding errors is eliminated completely.
Location error analysis of WSN in 3D complex terrain
Published in Journal of Control and Decision, 2023
The presence of obstacles hinders the communication path between SNs driving them to use NLOS signals for the localisation process resulting in lower localisation accuracy. Thus Bresensham's Line Drawing algorithm is used for finding the LOS signals by identifying the obstacle between the beacon position and the SN. Bresenham's line drawing algorithm (Fischer & Del Rio, 2004) is used in computer graphics to draw a line between two points. In this paper, the algorithm is modified and used for detecting the line of sight (i.e. the presence of any obstacle) between the beacon position and the SN. This is accomplished by drawing a virtual line between the beacon position and the SN. A visibility matrix at each SN for the beacon positions is created and the SN computes its location with the help of this visibility matrix. The visibility matrix can be computed as: Let denotes the beacon position and denote SN position. [X,Y,Z] denotes the set of points comprising the virtual line from to , where , , and . The visibility matrix has M rows (SNs) and N columns (Beacon positions) with values 1 or 0 stating 1 as the beacon position is visible while 0 as the beacon position is not visible as illustrated in Equation (1). where Z(X,Y) and are the heights of virtual line and terrain height at (X,Y) position respectively.