Applying Fuzzy Hough Transform for Identifying Honed Microgeometrical Surfaces

2019 ◽  
pp. 35-42
Author(s):  
Szilvia Nagy ◽  
Levente Solecki ◽  
Brigita Sziová ◽  
Balázs Sarkadi-Nagy ◽  
László T. Kóczy
Keyword(s):  
Hough Transform

ELLIPSOIDAL DROPLET DETECTION USING RANDOMIZED HOUGH TRANSFORM

2006 ◽  
Vol 16 (4) ◽  
pp. 365-378
Author(s):  
Y. J. Choo ◽  
B. S. Kang
Keyword(s):  
Hough Transform ◽  
Randomized Hough Transform

Modified Hough Transform in Problem of Increasing Probability of Target Detection in Electronic Surveillance Systems

2019 ◽  
Vol 24 (3) ◽  
pp. 291-300
Author(s):  
Evgeny I. Minakov ◽  
◽  
Aleksandr V. Meshkov ◽  
Elena O. Meshkova ◽  
◽  
...  
Keyword(s):  
Target Detection ◽  
Hough Transform ◽  
Surveillance Systems ◽  
Electronic Surveillance

The lane line detection based on the improved Hough transform

2014 ◽  
Author(s):  
Bo Yin ◽  
Haitao Wang ◽  
Yanping Cong
Keyword(s):  
Hough Transform ◽  
Line Detection ◽  
Lane Line

Concentric circle detection based on chord midpoint Hough transform

2009 ◽  
Vol 29 (7) ◽  
pp. 1937-1939 ◽  
Author(s):  
Lei WANG ◽  
Lin-qiang CHEN
Keyword(s):  
Hough Transform ◽  
Concentric Circle ◽  
Circle Detection

Using tow-steps Hough transform to detection ellipses

2008 ◽  
Vol 28 (7) ◽  
pp. 1761-1763 ◽  
Author(s):  
Jing-dong ZHAO
Keyword(s):  
Hough Transform

Fast Detection of Ground Penetrating Radar Objects Based on Cross Correlation and Hough Transform

2014 ◽  
Vol 35 (5) ◽  
pp. 1156-1162 ◽  
Author(s):  
Jian Wang ◽  
Xiao Yuan ◽  
Yu Li ◽  
Chun-lin Huang ◽  
Yi Su
Keyword(s):  
Ground Penetrating Radar ◽  
Hough Transform ◽  
Cross Correlation ◽  
Fast Detection ◽  
Ground Penetrating

An automatic identifying method of the squall line based on Hough transform

2021 ◽  
Author(s):  
Xing Wang ◽  
Hao-xuan Bian ◽  
Dai-li Qian ◽  
Chun-sheng Miao ◽  
Shao-wei Zhan
Keyword(s):  
Hough Transform ◽  
Squall Line

scholarly journals Improved Hough Transform and Total Variation Algorithms for Features Extraction of Wood

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 466
Author(s):  
Weiwei Du ◽  
Yarui Xi ◽  
Kiichi Harada ◽  
Yumei Zhang ◽  
Keiko Nagashima ◽  
...  
Keyword(s):  
Total Variation ◽  
Hough Transform ◽  
Annual Ring ◽  
Wood Quality ◽  
Volume Density ◽  
Low Noise ◽  
Impact Factors ◽  
Annual Rings ◽  
New Model ◽  
Model Combining

Research shows that the intensity impact factors of wood, such as late timber ratio, volume density and the intensity of itself, correlate with the width of wood annual rings. Therefore, extracting wood annual ring information from wood images is helpful for evaluating wood quality. During the past few years, many researchers have conducted defect detection by studying the information of wood images. However, there are few in-depth studies on the statistics and calculation of wood annual ring information. This study proposes a new model combining the Total Variation (TV) algorithm and the improved Hough transform to accurately measure the wood annual ring information. The TV algorithm is used to suppress image noise, and the Hough transform is for detecting the center of the wood image. Moreover, the edges of wood annual rings are extracted, and the statistical ring information is calculated. The experimental results show that the new model has good denoising capability, clearly extract the edges of wood annual rings and calculate the related parameters from the indoor wood images of the processed logs and the unprocessed low-noise logs.

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