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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.


Papers
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Journal ArticleDOI
TL;DR: A centroid measurement algorithm based on the adaptive thresholding and dynamic windowing method by utilizing image processing techniques for practical application of the digital SHWS in surface profile measurement that has better precision, repeatability, and stability compared with other commonly used centroid methods.
Abstract: A Shack-Hartmann wavefront sensor (SWHS) splits the incident wavefront into many subsections and transfers the distorted wavefront detection into the centroid measurement. The accuracy of the centroid measurement determines the accuracy of the SWHS. Many methods have been presented to improve the accuracy of the wavefront centroid measurement. However, most of these methods are discussed from the point of view of optics, based on the assumption that the spot intensity of the SHWS has a Gaussian distribution, which is not applicable to the digital SHWS. In this paper, we present a centroid measurement algorithm based on the adaptive thresholding and dynamic windowing method by utilizing image processing techniques for practical application of the digital SHWS in surface profile measurement. The method can detect the centroid of each focal spot precisely and robustly by eliminating the influence of various noises, such as diffraction of the digital SHWS, unevenness and instability of the light source, as well as deviation between the centroid of the focal spot and the center of the detection area. The experimental results demonstrate that the algorithm has better precision, repeatability, and stability compared with other commonly used centroid methods, such as the statistical averaging, thresholding, and windowing algorithms.

32 citations

Journal ArticleDOI
TL;DR: A novel shape signature, perimeter area function (PAF), that places all the vertexes of the triangle on the shape boundary can finely capture the local shape boundary information and outperforms the existing Fourier descriptors and Wavelet Fourier descriptor.

32 citations

Journal ArticleDOI
TL;DR: An improved two-stage GHT procedure for the recognition of overlapping objects that works well for complex objects under severely overlapping conditions and removes the false contribution of votes in the vote generation phase.

32 citations

Proceedings ArticleDOI
19 Nov 2010
TL;DR: This paper presents an algorithm for detection of traffic sign using color centroid matching, which has color classification rate of 100% while shape classification rate about 98% when tested on several outdoor images for traffic sign detection.
Abstract: Automatic traffic sign recognition system can help the driver to make a right decision at the right time for safe driving. This paper presents an algorithm for detection of traffic sign using color centroid matching. This algorithm detects the traffic sign from the images captured from the complex road environment. YCbCr color space is used for color segmentation to make the detection process independent of variable illumination characteristic. The proposed method extracts and classifies the detected sign according to colors of the traffic sign. The sign is extracted by considering the maximum distance of boundary pixels from centroid. The sign is further classified into its sub-group according to its shape. The minimum Euclidean distance classifier is used to detect the shape of sign. Perceptron Neural Network (NN) is employed to recognize the classified sign. Results show that the developed algorithm has color classification rate of 100% while shape classification rate about 98% when tested on several outdoor images for traffic sign detection. The overall recognition rate of the developed algorithm is observed around 92%.

32 citations

Patent
29 Aug 2008
TL;DR: In this paper, an information processor for precisely correcting a contact position or adjacent position, so as to allow the position to be close to not the detected contact position, but the contact position intended by a user, and to provide an information processing method therefor.
Abstract: PROBLEM TO BE SOLVED: To provide an information processor for precisely correcting a contact position or adjacent position, so as to allow the position to be close to not the detected contact position or adjacent position but the contact position or adjacent position intended by a user, and to provide an information processing method therefor. SOLUTION: The information processor includes: an adjacency detecting part 161 for acquiring a proximity value concerning contact or adjacency between an operation body and the surface of a display part; an angle calculating part 163 for ternarizing the proximity value, detecting the first area and the second area different from the first area, in response to the ternarized proximity value, and then, calculating the respective centroid positions of the first and second areas, so as to calculate the direction of a straight line connecting each centroid; a finger coordinate calculating part 162 for calculating the contact position or adjacent position between the operation body and the surface of the display part, based on the proximity value; and a correction finger coordinate calculating part 165 for calculating an indication position which is different from the contact position or adjacent position, based on the contact position or the adjacent position and the direction of the straight line connecting the first centroid and the second centroid. COPYRIGHT: (C)2010,JPO&INPIT

32 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023492
20221,001
2021184
2020202
2019269
2018271