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.

Automatic Power Lines Extraction Method from Airborne LiDAR Point Cloud

Abstract: This paper present a power lines automatic extraction method from airborne LiDAR point cloud.Firstly,ground points are removed by automatic filtering method based on fluctuant feature of terrain.Vegetation points,building points and part pylon points are also removed by dimensionality feature and direction feature.Secondly,2D Hough transform and least square fitting are used to fit center line equation of power lines.And then,the laser point of each power lines can be obtained by center line equation.In this step,power lines projection overlap in the horizontal plane are considered as well.Finally,block centroid calculation method is used to calculate 3Dnodes of each power lines.These nodes are used to output the power lines vector.The experimental result shows that the proposed method can extract complete power lines from airborne LiDAR point cloud.This method has some practical meaning for power line inspection.

Pulsar candidate selection using pseudo-nearest centroid neighbour classifier

Abstract: A typical characteristic of the pulsar candidate classification task is the class imbalance between true pulsars and false candidates. This imbalance has negative effects on traditional classification methods. In this study, we introduce a strategy using a scatter matrix-based class separability measure to estimate the harmfulness of class imbalance on pulsar candidate classification. The measure quantitatively describes the damage of the imbalanced situations on the pulsar candidate classification problem and provides some priori information to guide us to select an appropriate data processing method and to construct an effective classifier. After that, we present a non-parametric data exploration technique, a pseudo-nearest centroid neighbour classifier (PNCN), to identify credible pulsar candidates from pulsar survey data sets. The PNCN algorithm can effectively resolve the class imbalance problem and is applicable to data streams. The proposed algorithm is tested on High Time Resolution Universe Pulsar Survey (HTRU) 2 (obtained by an analysis of HTRU Medium Latitude data) and LOTAAS 1 (obtained from the LOFAR Tied-Array All-Sky Survey). The experimental results show that the proposed classifier can excellently identify the pulsars with high performance: the precision and the recall on HTRU 2 are 92.3 per cent and 83.1 per cent, and those on LOTAAS 1 are 97.4 per cent and 95.6 per cent, respectively; the false positive rate (FPR) on HTRU 2 is 0.7 per cent, on LOTAAS 1 is 0.03 per cent, which is an order of magnitude lower than the corresponding FPR obtained in Lyon et al. (2016) and Tan et al. (2018).

Visual device for robot

Abstract: PURPOSE:To obtain various kinds of information needed for the robot work to a subject of recognition which is shown with optional position and posture within a veiwfield, by teaching the point of measurement with a coordinate system proper to an object image CONSTITUTION:A visual device for robot is provided with a picture input part 101, a teaching processing part 102 and a recognition processing part 103 When the teaching is selected by a switch SW, both parts 101 and 102 work Then parts 101 and 103 work when the recognition is selected A form data extracting part 7 of the part 103 gives features to a subject image by means of the coordinates of the contour point stored in a contour point coordinate memory (b) and then obtains the area, the circumference length, the ratio between area and circumference length, the number of holes, etc for example to store them in a teaching form data storage memory (c) A centroid calculating part 8 obtains the centroid G of the subject image from the contour point coordinates; and an inertial main axis inclination calculating part 9 obtains the inclination theta of the inertial main axis of the subject image from the contour point coordinates The contents of these centroid and inclination are stored in a coordinate conversion storage memory (d)

Centroid frequency and spectral ratio integrated borehole seismic quality factor inversion method

Abstract: The invention discloses a centroid frequency and spectral ratio integrated borehole seismic quality factor inversion method, and the method comprises the steps: building a reversion equation for calculating a stratum attenuation coefficient through a spectral ratio; building a reversion equation between the movement amount of the centroid frequency and the stratum attenuation coefficient; building a combined reversion equation among the spectral ratio, the centroid frequency and the stratum attenuation coefficient; and solving a target function of combined inversion through employing a damping LSQR algorithm. The method maintains the stability of the results of a spectral ratio method, and the impact on the method from non-stratum factor amplitude attenuation is small. The method integrates the advantages of high calculation precision of a centroid frequency calculation method and the sensitive reflection of attenuation abnormity, makes the most of the frequency changes of attenuation of seismic waves, and builds the combined reversion equation for solving the attenuation coefficient through the centroid frequency and the spectral ratio for combined reversion. The method employs better spectral ratio information for the constraint reversion of the centroid frequency method, improves the reversion effect, effectively reduces the noises and other interference, and improves the stability of absorption attenuation parameter reversion results.

Image Indexing and Retrieval in Compressed Domain Using Color Clusters

Abstract: A compressed domain color-based image indexing method that avoids overheads associated with full decompression and color space transformation by operating in the YCbCr space has been presented. The proposed method performs a hard segmentation of the color space into predefined clusters based on perceptual similarity. A three dimensional color descriptor is generated by extracting the average intensity value of the Y, Cb and Cr components for each 8times8 DCT block. Each blocks descriptor is subsequently allocated to its corresponding cluster, whose centroid is updated using a weighted mean. The similarity measure is evaluated using a compact four dimensional feature vector from each cluster, which consists of the quantized centroid coordinates and the percentage contribution to the image composition by the cluster. Retrieval is performed by comparing the feature attributes of the clusters having significant membership in the query image, to those with the database images; the obtained matches are then integrated to evaluate the final ranking. The experimental results of the proposed model on a database of 7380 images are reported