Centroid

About: Centroid is a research topic. Over the lifetime, 4110 publications have been published within this topic receiving 53637 citations. The topic is also known as: barycenter (geometry) & geometric center of a plane figure.

Influence of thresholding on centroid statistics: full analytical description

Abstract: The centroid method is a common procedure for subpixel location that is applied to a large number of optical sensors. In practice, it is always accompanied by thresholding algorithms used to eliminate undesirable background that may decrease precision. We present a full analytical description of the interaction between centroiding and thresholding applied over an intensity distribution corrupted by additive Gaussian noise. An in depth analysis of the most outstanding statistical properties of this relation (mean and variance) is also presented by means of simulated and experimental data. This work provides fundamental concepts to the designers of sensors that are based on centroid measurements to allow them to use thresholding correctly before centroid computation.

Fast centroid algorithm for determining the surface plasmon resonance angle using the fixed-boundary method

Abstract: To simplify the algorithm for determining the surface plasmon resonance (SPR) angle for special applications and development trends, a fast method for determining an SPR angle, called the fixed-boundary centroid algorithm, has been proposed. Two experiments were conducted to compare three centroid algorithms from the aspects of the operation time, sensitivity to shot noise, signal-to-noise ratio (SNR), resolution, and measurement range. Although the measurement range of this method was narrower, the other performance indices were all better than the other two centroid methods. This method has outstanding performance, high speed, good conformity, low error and a high SNR and resolution. It thus has the potential to be widely adopted.

AWCL: Adaptive weighted centroid target localization algorithm based on RSSI in WSN

Abstract: Target localization and tracking is the canonical application of Wireless Sensor Networks. Unlike a centralized system, a sensor network is subject to a unique set of resource constraints such as limited on-board battery power and limited network communication bandwidth. So the traditional tracking algorithm can be directly used in WSN. Therefore efficient localization algorithms that consume less energy for computation and less bandwidth for communication are needed. The weighted centroid localization algorithm (WCL) based on RSSI is applied in most of actual systems. Only one uniform path loss exponent obtained through experiments is used to calculate the weights of nodes in general WCL. It is well known that the path loss exponent is the essential reflection of sensing surroundings. The actual sensing scenario can't be revealed in the traditional WCL algorithm, and therefore it is not appropriate that only one exponent is accepted all through the area covered by the sensor nodes. A new algorithm, adaptively weighted centroid localization (AWCL), is proposed in this paper. Firstly a more reasonable path loss exponent is adaptively estimated according to the surroundings where the target nodes situates. Secondly the target position will be calculated by using the weighted centroid method in which exponents estimated in the first stage are adopted. Theoretical analysis are presented to demonstrate the performance of the proposed localization method, the simulation results show that that the proposed algorithm outperforms the general WCL algorithm.