An automatic focusing algorithm

2002 ◽  
Vol 12 (6) ◽  
pp. 235-238 ◽  
Author(s):  
Sheng-Fuu Lin ◽  
You-Tasi Lin ◽  
Chien-Kun Su
Keyword(s):  
Automatic Focusing

An Automatic Focusing Algorithm Based on Blur Edge Width Detection in the Image

2012 ◽  
Vol 461 ◽  
pp. 470-473
Author(s):  
Fa Quan Zhang ◽  
Xin Yu Liu ◽  
Guo Fu Wang ◽  
Jin Cai Ye
Keyword(s):  
Wavelet Transform ◽  
Binary Image ◽  
Control Center ◽  
Automatic Focusing ◽  
Center Area ◽  
Computation Speed

An automatic focusing algorithm through detecting blur edge width via wavelet transform was proposed. To improve computation speed and fit for different scenes, the center area of the image and four golden points were selected as the focusing area. Wavelet module values of the focusing area were obtained through wavelet transform. The threshold to determine blur edge was selected by 50 percent of the wavelet module maximum in all wavelet module values. According to the threshold, the binary image of the blur edge was achieved. Area and girth of the blur edge were calculated respectively, and blur edge width was computed by area and girth. The control center computed steps according to blur edge width to adjust the lens, and the focusing motor operated corresponding steps received from the control center. Therefore, an automatic focusing procedure was implemented. Results show that the automatic focusing algorithm is quick and effective.

Automatic focusing for a 675 GHz imaging radar with target standoff distances from 14 to 34 meters

2013 ◽  
Author(s):  
Adrian Tang ◽  
Ken B. Cooper ◽  
Robert J. Dengler ◽  
Nuria Llombart ◽  
Peter H. Siegel
Keyword(s):  
Imaging Radar ◽  
Automatic Focusing

Ultrafast hardware-based focal law calculator for automatic focusing

2015 ◽  
Vol 74 ◽  
pp. 1-7 ◽  
Author(s):  
Jorge F. Cruza ◽  
Jorge Camacho ◽  
Jose M. Moreno ◽  
Carlos Fritsch
Keyword(s):  
Automatic Focusing

Development of a Compact Automatic Focusing System for a Neurosurgical Laser Instrument

2007 ◽  
pp. 57-66
Author(s):  
Masafumi Noguchi ◽  
Eisuke Aoki ◽  
Etsuko Kobayashi ◽  
Shigeru Omori ◽  
Yoshihiro Muragaki ◽  
...  
Keyword(s):  
Automatic Focusing

Research on the Tool Images Evaluation Based on Auto-Focus Technology

2011 ◽  
Vol 411 ◽  
pp. 478-482
Author(s):  
Yue Shen Lai ◽  
Meng Shi ◽  
Jun Wei Tian ◽  
Gang Cheng
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Color Images ◽  
Processing Technology ◽  
Evaluation Function ◽  
Fast Speed ◽  
Evaluation Functions ◽  
Green Component ◽  
Automatic Focusing

Accurate and efficient image-clarity evaluation function which adopts digital image processing technology is the key to achieving automatic focusing. The different evaluation functions are adopted for different images. By converting color images to grayscale, and comparing them with the green component which extract from the color images, it is found that using the gray image can get a much better results and an evaluation function is built which is used for tool images. Experiments prove that the used algorithm has a good single peak, accuracy, stability, and fast speed.

Photoelectric automatic focusing system based on interference

2001 ◽  
Vol 36 (4) ◽  
pp. 345-353 ◽  
Author(s):  
T.G. Liu ◽  
H.Y. Cai ◽  
F.L. Zhang ◽  
R.A. Lessard ◽  
Y.M. Zhang
Keyword(s):  
Automatic Focusing

Research of the Evaluation Function Based on Improved Neighborhood Difference Operator

2013 ◽  
Vol 433-435 ◽  
pp. 358-361
Author(s):  
Cheng Yun Wang ◽  
Long Ye
Keyword(s):  
Digital Video ◽  
Difference Operator ◽  
Robot Vision ◽  
Evaluation Function ◽  
Good Sensitivity ◽  
Noise Resistance ◽  
Key Technology ◽  
Video Systems ◽  
Automatic Focusing

Automatic focusing is one of the key technology of robot vision and digital video-systems, while play an important role in determining the quality of image. The performance of focusing depends on whether the evaluation function has unbiasedness, unimodality and noise resistance. This paper proposes a new evaluation function algorithm by improving image clarity-evaluation function of the traditional neighborhood difference operator. Compared with the existing algorithm, the results of experiments demonstrated the new algorithm has a good sensitivity, timeliness, good anti-noise ability and stability during the automatic focusing process.

Automatic focusing of scanning microscopes

1972 ◽  
Vol 104 (1) ◽  
pp. 225-226 ◽  
Author(s):  
B. Goel ◽  
R. Eggmann
Keyword(s):  
Automatic Focusing

Research of the Evaluation Function Based on Improved Neighborhood Difference Operator

2013 ◽  
Vol 427-429 ◽  
pp. 1566-1569
Author(s):  
Cheng Yun Wang ◽  
Long Ye
Keyword(s):  
Digital Video ◽  
Difference Operator ◽  
Robot Vision ◽  
Evaluation Function ◽  
Good Sensitivity ◽  
Noise Resistance ◽  
Key Technology ◽  
Video Systems ◽  
Automatic Focusing

Automatic focusing is one of the key technology of robot vision and digital video-systems, while play an important role in determining the quality of image. The performance of focusing depends on whether the evaluation function has unbiasedness, unimodality and noise resistance. This paper proposes a new evaluation function algorithm by improving image clarity-evaluation function of the traditional neighborhood difference operator. Compared with the existing algorithm, the results of experiments demonstrated the new algorithm has a good sensitivity, timeliness, good anti-noise ability and stability during the automatic focusing process.

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