Topic
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.
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29 Jun 2010
TL;DR: In this paper, a document alteration detection method compares a target image with an original image using a two-step process, where the original and target images are divided into connected image components and their centroids are obtained.
Abstract: A document alteration detection method compares a target image with an original image using a two-step process. In the first step, the original and target images are divided into connected image components and their centroids are obtained, and the centroids of the image components in the original and target images are compared. Each centroid in the target image that is not in the original image is deemed to represent an addition, and each centroid in the original image that is not in the target image is deemed to represent a deletion. In the second step, sub-images containing the image components corresponding to each pair of matching centroids in the original and target images are compared to detect any alterations.
13 citations
TL;DR: It is concluded that the human visual system assigns position tags using centroids not peaks of luminance distributions for gabors, however this is not the case for Gaussian blobs, where a measure closer to the midpoint is used for the authors' stimulus arrangement.
13 citations
01 Dec 2014
TL;DR: The modeling concept of the "Base Centroid Virtual Manipulator (BCVM) for free-floating multi-arm space robotic systems was proposed and the trajectory planning method of the balance arm was addressed.
Abstract: Due to the dynamic interaction, the motion of the arms alters the attitude and position of the base To stabilize the centroid position of the base during on-orbital manipulation, we proposed the modeling concept of the "Base Centroid Virtual Manipulator (BCVM)" for free-floating multi-arm space robotic systems Correspondingly, the trajectory planning method of the balance arm was addressed The movement direction and the position of each joint of the BCVM are the same as those of the real space manipulator (SM) The end-effector's position of the BCVM denotes the equivalent centroid of the corresponding SM By resolving the position-level kinematic equations, the singularity-free trajectory of the balance arm was then planned Based on the BCVM model, the stabilization ability of a given balance arm can be easily determined by analyzing the workspace of the BCVM Furthermore, the configuration and the mass properties of the balance arm can be optimized Simulation results of joint trajectory tracking task verified the proposed model and method
13 citations
TL;DR: In this paper, the bias error for different correlation peak-finding algorithms and types of sub-aperture images is quantified and a practical solution to minimize its effects is proposed. But these solutions only allow partial bias corrections.
Abstract: Shack-Hartmann wavefront sensing relies on accurate spot centre measurement. Several algorithms were developed with this aim, mostly focused on precision, i.e. minimizing random errors. In the solar and extended scene community, the importance of the accuracy (bias error due to peak-locking, quantisation or sampling) of the centroid determination was identified and solutions proposed. But these solutions only allow partial bias corrections. To date, no systematic study of the bias error was conducted. This article bridges the gap by quantifying the bias error for different correlation peak-finding algorithms and types of sub-aperture images and by proposing a practical solution to minimize its effects. Four classes of sub-aperture images (point source, elongated laser guide star, crowded field and solar extended scene) together with five types of peak-finding algorithms (1D parabola, the centre of gravity, Gaussian, 2D quadratic polynomial and pyramid) are considered, in a variety of signal-to-noise conditions. The best performing peak-finding algorithm depends on the sub-aperture image type, but none is satisfactory to both bias and random errors. A practical solution is proposed that relies on the anti-symmetric response of the bias to the sub-pixel position of the true centre. The solution decreases the bias by a factor of ~7 to values of < 0.02 pix. The computational cost is typically twice of current cross-correlation algorithms.
13 citations
TL;DR: In this paper , a new motion feature is introduced to describe the moving melt pool, and the distance between the centroid and the boundary of melt pool is calculated from the unfolded clockwise at a step angle, which constructs a high dimensional feature vector as the motion features.
13 citations