A Multi-objective Robust Ellipse Fitting Algorithm

2017 ◽  
pp. 141-158
Author(s):  
Heriberto Cruz Hernández ◽  
Luis Gerardo de la Fraga
Keyword(s):  
Ellipse Fitting ◽  
Multi Objective ◽  
Fitting Algorithm

AN IMPROVED RANDOM WALK SEGMENTATION ON THE LUNG NODULES

2013 ◽  
Vol 06 (06) ◽  
pp. 1350043 ◽  
Author(s):  
LI GUO ◽  
YUNTING ZHANG ◽  
ZEWEI ZHANG ◽  
DONGYUE LI ◽  
YING LI
Keyword(s):  
Random Walk ◽  
Lung Nodule ◽  
Texture Feature ◽  
Ellipse Fitting ◽  
Lung Nodule Detection ◽  
Random Walk Algorithm ◽  
Fitting Algorithm ◽  
Nodule Detection ◽  
Walk Algorithm ◽  
Automatic Technique

In this paper, we proposed a semi-automatic technique with a marker indicating the target to locate and segment nodules. For the lung nodule detection, we develop a Gabor texture feature by FCM (Fuzzy C Means) segmentation. Given a marker indicating a rough location of the nodules, a decision process is followed by applying an ellipse fitting algorithm. From the ellipse mask, the foreground and background seeds for the random walk segmentation can be automatically obtained. Finally, the edge of the nodules is obtained by the random walk algorithm. The feasibility and effectiveness of the proposed method are evaluated with the various types of the nodules to identify the edges, so that it can be used to locate the nodule edge and its growth rate.

A Vision Recognition Method of Wheel's Pose and Position Parameters in Bench Testing

2013 ◽  
Vol 427-429 ◽  
pp. 45-48
Author(s):  
Xin Jia ◽  
Hsin Guan
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Rigid Body ◽  
Processing Method ◽  
Least Square ◽  
Body Motion ◽  
Ellipse Fitting ◽  
Recognition Method ◽  
Fitting Algorithm ◽  
Bench Testing

IA method is proposed here to recognize wheels pose and position parameters with computer vision aiming to the need of measuring wheel moving track in suspension bench testing. Firstly, several markers are fit on the target wheel manually. Secondly, image coordinates of character points is calculated with image processing method and least square ellipse fitting algorithm. At last, wheels pose and position parameters are calculated with rigid body motion POSIT algorithm, and then wheel moving track is measured in test. The algorithm of wheels pose and position parameters in bench testing based on the computer vision here will supply the base under the realization of the moving wheels pose and position parameters recognizing in real time.

Advanced Ellipse Fitting Algorithm Based on ADMM and Hybrid BFGS

2021 ◽  
pp. 1-1
Author(s):  
Xia Zhang ◽  
Ding Liu ◽  
Xue Wang ◽  
Xinyu Zhang
Keyword(s):  
Ellipse Fitting ◽  
Fitting Algorithm

Telephoto structured laser autocollimation based on common-path compensation method and ellipse fitting algorithm

2020 ◽  
Vol 59 (02) ◽  
pp. 1
Author(s):  
Weizhe Cheng ◽  
Haobo Cheng ◽  
Yongfu Wen ◽  
Yunpeng Feng ◽  
Yan Guo ◽  
...  
Keyword(s):  
Compensation Method ◽  
Ellipse Fitting ◽  
Common Path ◽  
Fitting Algorithm

Application of Masking and Ellipse Fitting in Pupil Localization

2013 ◽  
Vol 798-799 ◽  
pp. 614-619
Author(s):  
Jing Yin ◽  
Na Na Zhang ◽  
Xiang Wu ◽  
Wai Yun Li
Keyword(s):  
Ellipse Fitting ◽  
Human Face ◽  
Human Face Recognition ◽  
Pupil Center ◽  
Fitting Algorithm ◽  
Center Position ◽  
Pupil Localization ◽  
Fitting In ◽  
Human Eyes ◽  
Eyes Detection

The human eyes feature plays an important role in the human face feature extraction and the human face recognition. It can be used to correct the human face posture and locate the other face key features by the coordinates of the eyes on the human face. In this paper, we train the human eyes detection cascade strong classifier which be used to detect the human eyes position on the human face , and then locate the pupil center position by making use of the ellipse fitting algorithm and the human eyes mask templates. The experimental results show that these algorithms which be used in this paper can accurately locate the pupil center position.

scholarly journals Study on duck weight estimation by using image processing

2020 ◽  
Vol 187 ◽  
pp. 02001
Author(s):  
Phatpisey Lieng ◽  
Kiattisak Sangpradit
Keyword(s):  
Live Weight ◽  
Prediction Equation ◽  
The Body ◽  
Ellipse Fitting ◽  
Weight Estimation ◽  
Acceptable Error ◽  
Measured Weight ◽  
Fitting Algorithm ◽  
Weight Prediction ◽  
Top View

The objective of this research was to process digital image to investigate the possibility of ducks weight estimation based on the software LabVIEW with the vision builder. In this study the images were record by the top-view camera. An ellipse fitting algorithm was applied to localize ducks within the stall. Estimating duck weight consists of these steps. First, image acquisition. Second, counts pixel of the samples. Third calculate duck weight by using samples pixel as the output. Results from this study showed that, the estimated ducks weight by using digital photos had 3.27% of the error when compare to the measured weight. The correlation coefficient of the body weight prediction equation from a comparison between measured (absolute) and estimated by camera for all duck is clearly high (R2=0.91). It was found that the system able to estimate duck weight with an acceptable error. So we can develop this research processing or build up the automatic sorting duck in the future. This method operated pretty well in prophecy live weight.

Research on Roadbed Settlement Measurement with Laser Spot Detection Based on Ellipse Fitting

2014 ◽  
Vol 530-531 ◽  
pp. 113-116
Author(s):  
Jing Hong Xing ◽  
Xiang Wei Li ◽  
Lang Tao Zhao
Keyword(s):  
Curve Fitting ◽  
Optical Axis ◽  
Laser Spot ◽  
Ellipse Fitting ◽  
Edge Extraction ◽  
Circle Fitting ◽  
Spot Center ◽  
Spot Detection ◽  
Fitting Algorithm ◽  
Canny Edge

Detecting the location offset of laser spot center method to monitor roadbed settlement is a kind of portable, easy to layout method. Detection laser spot center offset, we can use gravity, circle fitting, ellipse fitting and Gaussian curve fitting, etc method. Gravity algorithm is only involves basic arithmetic and low precise, and ellipse fitting is higher precise. Because of the angle between the optical axis and the target, the laser spot is more approximate as a ellipse. Using the ellipse fitting algorithm, Sub-pixel precise threshold segmentation and Canny edge extraction we obtained an ideal monitoring precise of the roadbed settlement.

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