scholarly journals A Mean Shift Algorithm for Drift Correction in Localization Microscopy

2021 ◽  
pp. 100008
Author(s):  
Frank J. Fazekas ◽  
Thomas R. Shaw ◽  
Sumin Kim ◽  
Ryan A. Bogucki ◽  
Sarah L. Veatch
Keyword(s):  
Mean Shift ◽  
Drift Correction ◽  
Localization Microscopy ◽  
Mean Shift Algorithm

scholarly journals A Mean Shift Algorithm for Drift Correction in Localization Microscopy

2021 ◽  
Author(s):  
Frank J Fazekas ◽  
Thomas R Shaw ◽  
Sumin Kim ◽  
Ryan A Bogucki ◽  
Sarah L Veatch
Keyword(s):  
Single Molecule ◽  
Mean Shift ◽  
Time Lapse ◽  
Drift Correction ◽  
Localization Microscopy ◽  
Mean Shift Algorithm ◽  
Peak Finding ◽  
Localization Precision ◽  
Time Lapse Imaging ◽  
Single Molecule Localization Microscopy

Single molecule localization microscopy (SMLM) techniques transcend the diffraction limit of visible light by localizing isolated emitters sampled stochastically. This time-lapse imaging necessitates long acquisition times, over which sample drift can become large relative to the localization precision. Here we present a novel, efficient, and robust method for estimating drift using a simple peak-finding algorithm based on mean shifts that is effective for SMLM in 2 or 3 dimensions.

Automatic vertebra segmentation based on graph cut and mean shift algorithm

2011 ◽  
Vol 31 (3) ◽  
pp. 760-762
Author(s):  
Ji LIU ◽  
Xiao-dong KANG ◽  
Fu-cang JIA
Keyword(s):  
Mean Shift ◽  
Graph Cut ◽  
Mean Shift Algorithm

The mean shift algorithm and its relation to kernel regression

2016 ◽  
Vol 348 ◽  
pp. 198-208 ◽  
Author(s):  
Youness Aliyari Ghassabeh ◽  
Frank Rudzicz
Keyword(s):  
Mean Shift ◽  
Kernel Regression ◽  
Mean Shift Algorithm ◽  
The Mean

Video Vehicle Tracking Based on Improved Mean-Shift Algorithm

2011 ◽  
Vol 179-180 ◽  
pp. 1408-1411
Author(s):  
Wei Bin Chen ◽  
Xin Zhang ◽  
Su Qin Luo
Keyword(s):  
Clustering Algorithm ◽  
Mean Shift ◽  
Vehicle Tracking ◽  
Absolute Difference ◽  
Mean Shift Algorithm ◽  
Invariant Moments ◽  
Mean Shift Clustering ◽  
Video Frames ◽  
Detection Technology ◽  
Background Area

An improved Mean-Shift-based Video vehicle tracking algorithm was proposed and which can improve the real-time and accuracy of the vehicle detection technology in the application. First, it eliminates the disturbance from unrelated background by mathematical morphology operation between a traffic image and the mask of fixed background area .Then the image sequences are simulated by absolute difference of adaptive threshold for detecting latent target. At last, clusters video frames with similar characteristics which are regarded of the invariant moments vectors by Mean Shift clustering algorithm. Experimental results shown that the improved algorithm has advantages of reducing king region of vehicle matching and vehicle complete occlusion.

A dual-mode mean-shift algorithm

2008 ◽  
Author(s):  
Shih-Yu Chiu ◽  
Jia-Rui Zhang ◽  
Leu-Shing Lan
Keyword(s):  
Mean Shift ◽  
Dual Mode ◽  
Mean Shift Algorithm
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