scholarly journals A map-based normalized cross correlation algorithm using dynamic template for vision-guided telerobot

2017 ◽  
Vol 9 (9) ◽  
pp. 168781401772883 ◽  
Author(s):  
Hui Zhang ◽  
Aiguo Song
IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 65199-65211
Author(s):  
Abdulla Mohamed ◽  
Phil F. Culverhouse ◽  
Angelo Cangelosi ◽  
Chenguang Yang

2013 ◽  
Vol 29 (2) ◽  
pp. 165-173 ◽  
Author(s):  
Stephen J. Pearson ◽  
Tim Ritchings ◽  
Ahmad S.A. Mohamed

The work describes an automated method of tracking dynamic ultrasound images using a normalized cross-correlation algorithm, applied to the patellar and gastrocnemius tendon. Displacement was examined during active and passive tendon excursions using B-mode ultrasonography. In the passive test where two regions of interest (2-ROI) were tracked, the automated tracking algorithm showed insignificant deviations from relative zero displacement for the knee (0.01 ± 0.04 mm) and ankle (–0.02 ± 0.04 mm) (P> .05). Similarly, when tracking 1-ROI the passive tests showed no significant differences (P> .05) between automatic and manual methods, 7.50 ± 0.60 vs 7.66 ± 0.63 mm for the patellar and 11.28 ± 1.36 vs 11.17 ± 1.35 mm for the gastrocnemius tests. The active tests gave no significant differences (P> .05) between automatic and manual methods with differences of 0.29 ± 0.04 mm for the patellar and 0.26 ± 0.01 mm for the gastrocnemius. This study showed that automatic tracking of in vivo displacement of tendon during dynamic excursion under load is possible and valid when compared with the standardized method. This approach will save time during analysis and enable discrete areas of the tendon to be examined.


Author(s):  
Ismael Lopez Sanchez ◽  
Miguel Angel Rosas Galaviz ◽  
Damian Gomez Herrera ◽  
Luis Rizo Dominguez

2013 ◽  
Vol 860-863 ◽  
pp. 2800-2803
Author(s):  
Yu Bing Dong ◽  
Ming Jing Li ◽  
Guo Xin Li

Using logical criterion based on the characteristics of binary image, the normalized cross-correlation algorithm is improved. First, the binary of gray image is carried out. The target and the background are made a distinction between 0 and 1. Second, through the logic correlation matching, two images of the same location value equal to 1, otherwise 0. Finally, the correlation coefficient is calculated. The experimental results show that the improved normalized cross-correlation algorithm can speed up the matching, without affecting the accuracy of the matching.


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