Papers by Keyword: Centroid Algorithm

Abstract: To address the problem that anchor ratio had a strong impact on localization error and coverage in centroid algorithm in wireless sensor network (WSN), an improved algorithm was proposed. This algorithm differentiated the priority of the unknown nodes according to the distance between unknown nodes and anchors. The algorithm was proposed to locate the unknown nodes with the highest priority, and then update them to new anchors. Finally, the rest unknown nodes are located by centroid algorithm. The simulation results show that this improved algorithm can effectively reduce the localization error and enhance the coverage when the anchor ratio is lower.

Abstract: In order to measure the parallelism of two thin parallel beams in multi-axis interferometers and differential interferometers, the autocollimation principle was used by locating a CCD at the focal plane of collimation lens, the two beams converge on CCD image plane at different points when they are not parallel, and the distance between the two converging points is used to calculate the parallelism of the two beams. To achieve high accuracy and low system error, the CCD defocus and tilt should be strictly controlled according to the accuracy requirement. A centroid algorithm with grey threshold was used to reduce the influence of image noise. A beam-selected structure was designed to let the two beams converge to the CCD image plane in sequence to avoid superposition of beam spots. An experimental setup is built to verify the validity of the method. Experimental results show that the system has a centroid position resolution of 0.05 arcsec and a centroid position stability of 0.4 arcsec. It is therefore concluded that the method can be used to measure parallelism that is more than few arcsecs for two thin beams. Moreover, the measuring accuracy of this method can be improved when higher centroid position stability is achieved.

Abstract: This paper researches on the detection and tracking technology of ship intrusion and remaining based on the special surveillance video scenes of sea. A ship detection and tracking method that combines the adaptive background subtraction with centroid algorithm is proposed. Compared with the method of edge orientation histogram, the method proposed in this paper shows a lower computational complexity and a better real-time performance. The experiment demonstrate that this method has a high degree of accuracy. And it makes a realization of detecting and tracking of ship intrusion and remaining within the surveillance sea.

Abstract: With the advent of Internet of things, more and more applications require location-based services. This paper firstly introduces classification of positioning technology, then some of the commonly used positioning technology is discussed, and finally the advantages and disadvantages of them are analyzed and compared.

Abstract: This paper introduces the first wireless sensor network node localization in two ways, one is based on the RSSI ranging approach, and the other is based on the weighted centric location algorithm, as a result of environmental factors, the same RSSI value the distance ，but the corresponding values are not always the same, these two methods do not consider the environmental impact to the RSSI value. Therefore, we consider combining the distance and signal strength information as a reference to correct each beacon node weights， in order to improve positioning accuracy.

Abstract: Localization has been a major challenge in Wireless Sensor Networks (WSNs), especially for the applications requiring the accurate position of the sensed information. In this paper, we propose a new localization algorithm based on the Centroid algorithm and the DV-Hop algorithm to improve the positioning accuracy without increasing any extra hardware for sensor nodes. This paper firstly analyzed the advantages and disadvantages of the centroid algorithm and the DV-Hop algorithm. Then we put forward an iterated hybrid algorithm, which is comprised of three steps. Firstly, obtaining the initial location of each unknown node by using the centroid algorithm; secondly, computing the distances among each unknown node to the anchor nodes based on the DV-Hop algorithm; finally, Taylor Series Expansion (TSE) algorithm is utilized to estimate coordinate of each unknown node. Simulation results show that our iterated hybrid algorithm has better positioning accuracy.

Abstract: Wireless sensor networks more complex in the marine environment than in terrestrial environments, the independent positioning mechanism can reduce the difficulty of modeling. The study on underwater acoustic sensor network node distribution of two-dimensional and three-dimensional respectively and the establishment relation function of the distance of beacon nodes and unknown nodes which based on in the traditional centroid algorithm idea. Using Taylor series can reduce the complexity computing of nodes who sensitive to energy because of its linear approximation in a manner. Because the genetic algorithm fitness function only interested in building the corresponding function, optimizing the established function. Simulation results show that: it can achieve the nodes self-localization effectively both in two- dimension and three-dimension that the distance formulas between nodes are liberalized by Taylor series and optimized by genetic algorithms.

Abstract: By giving a centroid algorithm to extract pixel coordinates of each circle in the center of a circle under the coordinates, through the coordinate transformation the image coordinates can be obtained. Based on the data obtained from above to verify the model, from the specific data of the relative error, absolute error and error propagation theory to discuss the algorithm accuracy and stability. Finally using the least square method, according to the mean square error criteria for the establishment of a minimum of three-dimensional coordinate system fixed relative position of two cameras, binocular positioning mathematical models and by discussing the nature of matrix and the relationship between the relative position of the camera to calibrate the binocular digital camera.

Abstract: Digital cameras have been widely used in the areas of road transportation, railway transportation as well as security system. To address the position of digital camera in these fields this paper proposed a geometry calibration method based on feature point extraction of arbitrary target. Under the meaning of the questions, this paper first defines four kinds of coordinate system, that is the world coordinate system. The camera's optical center of the coordinate system is the camera coordinate system, using the same point in different coordinate system of the coordinate transformation to determine the relationship between world coordinate system and camera coordinate. And thus determine the camera's internal parameters and external parameters, available transformation matrix and translation vector indicated by the camera's internal parameters of the external parameters and the establishment of a single camera location model. According to the model, using the camera's external parameters to be on the target circle center point in the image plane coordinates.