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.

Anomaly detection in enterprise threat detection

Abstract: A selection of data types is defined from available log data for an evaluation of events associated with an entity. One or more evaluations associated with the entity are defined and reference data is generated from the selection of data types based on the one or more defined evaluations. The one or more evaluations are grouped into a pattern. A three dimensional (3D) score diversity diagram visualization is initialized for display in a graphical user interface, where a point representing the entity in the visualization is localized in 3D space at a coordinate based on two-dimensional (2D) coordinates in a 2D coordinate system of a centroid of the calculated area of a polygon placed to into the 2D coordinate system and defined by the values of each evaluation associated with the entity.

Classification of satellite images using new Fuzzy cluster centroid for unsupervised classification algorithm

Abstract: Vagueness in the boundaries of land cover classes is one of the important problems in the image classification. Fuzzy c means (FCM) is a traditional clustering algorithm that has been widely used in the satellite image classification. However, this algorithm has the drawback of falling into a local minimum and it needs much time to accomplish the classification for a large data set. In order to overcome these drawbacks, a New Fuzzy Cluster Centroid (NFCC) for unsupervised classification algorithm is proposed to improve the traditional FCM and fuzzy weighted c means (FWCM) algorithm. In this work a, new objective function is formulated by adding the new term along with the distance between the pixels and cluster centers in the spectral domain. This new term is formulated by multiplying the Lagrange's multiplier with the membership values of the pixel for a particular class is subtracted with one. It gives weightage to the instance of a particular pixel. The inclusion of the fuzzy centroid for each cluster increases the stability of the algorithm and the inclusion of the new term reduces the number of iterations for image classification. The technique was applied to both IKONOS and QuickBird images. Overall accuracy statistics indicates that NFCC for unsupervised classification algorithm increases the accuracy of the satellite image classification at the pixel level.

Adaptive suboptimum detection of an optical pulse-position-modulation signal with a detection matrix and centroid tracking

Abstract: In some applications of optical communication systems, such as satellite optical communication and atmospheric optical communication, the optical beam wanders on the detector surface as a result of vibration and turbulence effects, respectively. The wandering of the beam degrades the communication system performance. In this research, we derive a mathematical model of an optical communication system with a detection matrix to improve the system performance for direct-detection pulse-position modulation. We include a centroid tracker in the communication system model. The centroid tracker tracks the center of the beam. Using the position of the beam center and an a priori model of the beam spreading, we estimate the optical power on each pixel (element) in the detection matrix. Using knowledge of the amplitudes of signal and noise in each pixel, we tune adaptively and separately the gain of each individual pixel in the detection matrix for communication signals. Tuning the gain is based on the mathematical model derived in this research. This model is defined as suboptimal, owing to some approximations in the development and is a suboptimum solution to the optimization problem of n multiplied by m free variables, where n, m are the dimensions of the detection matrix. Comparison is made between the adaptive suboptimum model and the standard model. From the mathematical analysis and the results of the comparison it is clear that this model significantly improves communication system performance.