Automatic location editing of assembly robot programs

2011 ◽  
pp. 55-72 ◽  
Author(s):  
M. Woollett
Keyword(s):  
Automatic Location

scholarly journals An Evaluation of Cellular Neural Networks for the Automatic Identification of Cephalometric Landmarks on Digital Images

2009 ◽  
Vol 2009 ◽  
pp. 1-12 ◽  
Author(s):  
Rosalia Leonardi ◽  
Daniela Giordano ◽  
Francesco Maiorana
Keyword(s):  
Neural Networks ◽  
Cellular Neural Networks ◽  
Automatic Identification ◽  
Cephalometric Analysis ◽  
X Rays ◽  
X Ray ◽  
Automatic Location ◽  
Landmark Identification ◽  
The Mean ◽  
Analogue To Digital

Several efforts have been made to completely automate cephalometric analysis by automatic landmark search. However, accuracy obtained was worse than manual identification in every study. The analogue-to-digital conversion of X-ray has been claimed to be the main problem. Therefore the aim of this investigation was to evaluate the accuracy of the Cellular Neural Networks approach for automatic location of cephalometric landmarks on softcopy of direct digital cephalometric X-rays. Forty-one, direct-digital lateral cephalometric radiographs were obtained by a Siemens Orthophos DS Ceph and were used in this study and 10 landmarks (N, A Point, Ba, Po, Pt, B Point, Pg, PM, UIE, LIE) were the object of automatic landmark identification. The mean errors and standard deviations from the best estimate of cephalometric points were calculated for each landmark. Differences in the mean errors of automatic and manual landmarking were compared with a 1-way analysis of variance. The analyses indicated that the differences were very small, and they were found at most within 0.59 mm. Furthermore, only few of these differences were statistically significant, but differences were so small to be in most instances clinically meaningless. Therefore the use of X-ray files with respect to scanned X-ray improved landmark accuracy of automatic detection. Investigations on softcopy of digital cephalometric X-rays, to search more landmarks in order to enable a complete automatic cephalometric analysis, are strongly encouraged.

Automatic location of disruption times in JET

2014 ◽  
Vol 85 (11) ◽  
pp. 11D826
Author(s):  
R. Moreno ◽  
J. Vega ◽  
A. Murari ◽  
Keyword(s):  
Automatic Location

Automatic location of anatomical points in head MRI based on the scale attention hourglass network

2021 ◽  
Vol 29 (9) ◽  
pp. 2278-2286
Author(s):  
Sai LI ◽  
◽  
Hao-jiang LI ◽  
Li-zhi LIU ◽  
Tian-qiao ZHANG ◽  
...  
Keyword(s):  
Automatic Location

scholarly journals Automated Control of Surface Defects on Ceramic Tiles Using 3D Image Analysis

Materials ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1250
Author(s):  
Andrzej Sioma
Keyword(s):  
Image Analysis ◽  
Surface Defects ◽  
Three Dimensional ◽  
3D Image ◽  
Ceramic Tiles ◽  
Production Lines ◽  
Automated Control ◽  
Automatic Location ◽  
Surface Image ◽  
Tile Surface

This paper presents a method of acquisition and analysis of three-dimensional images in the task of automatic location and evaluation of defects on the surface of ceramic tiles. It presents a brief description of selected defects appearing on the surface of tiles, along with the analysis of their formation. The paper includes the presentation of the method of constructing a 3D image of the tile surface using the Laser Triangulation Method (LTM), along with the surface imaging parameters employed in the research. The algorithms of three-dimensional surface image analysis of ceramic tiles used in the process of image filtering and defect identification are presented. For selected defects, the method of measuring defect parameters and the method of visualization of defects on the surface are also presented. The developed method was tested on defective products to confirm its effectiveness in the field of quick defect detection in automated control systems installed on production lines.

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