A Lane Detection Technique Based on Adaptive Threshold Segmentation of Lane Gradient Image

2018 ◽  
Author(s):  
Ma Li-Yong ◽  
Hua Chun-Sheng ◽  
He Yu-Qing ◽  
Liu Yun-Jing ◽  
Yan Pei-Lun
Keyword(s):  
Adaptive Threshold ◽  
Lane Detection ◽  
Detection Technique ◽  
Threshold Segmentation ◽  
Gradient Image

An Improved Adaptive Threshold Skin Color Model

2014 ◽  
Vol 610 ◽  
pp. 358-361
Author(s):  
Hong Wei Di ◽  
Wei Xu
Keyword(s):  
Skin Color ◽  
Adaptive Threshold ◽  
Experimental Results ◽  
Color Model ◽  
Threshold Segmentation ◽  
Change Rate ◽  
Skin Segmentation ◽  
Strong Robustness ◽  
Skin Color Model ◽  
Optimum Threshold

To solve the problem that traditional threshold segmentation model is not very robust in skin segmentation under different skin colors and different illuminations, an improved adaptive skin color model is proposed. This model detects the change rate of the skin color pixels by modifying the certain threshold while fixing others, then selects the optimum threshold adaptively. The experimental results show that this algorithm can effectively distinguish skin color regions and background regions, and has strong robustness on light disturbance.

Research on the High-Speed Object Shadowgraph Image Processing Method Based on Adaptive Threshold Segmentation

2013 ◽  
Vol 325-326 ◽  
pp. 1571-1575
Author(s):  
Fang Wang ◽  
Zong Wei Yang ◽  
De Ren Kong ◽  
Yun Fei Jia
Keyword(s):  
Image Processing ◽  
High Speed ◽  
Center Of Mass ◽  
Image Data ◽  
Ccd Camera ◽  
Adaptive Threshold ◽  
Processing Method ◽  
Laser Source ◽  
Feature Points ◽  
Threshold Segmentation

Shadowgraph is an important method to obtain the flight characteristics of high-speed object, such as attitude and speed etc. To get the contour information of objects and coordinates of feature points from shadowgraph are the precondition of characteristics analysis. Current digital shadowgraph system composed of CCD camera and pulsed laser source is widely used, but still lack of the corresponding method in image processing. Therefore, the selection of an effective processing method in order to ensure high effectiveness and accuracy of image data interpretation is an urgent need to be solved. According to the features of shadowgraph, a processing method to realize the contour extraction of high-speed object by adaptive threshold segmentation is proposed based on median filtering in this paper, and verified with the OpenCV in VC environment, the identification process of the feature points are recognized. The result indicates that by using this method, contours of high-speed objects can be detected nicely, to combine relevant algorithm, the pixel coordinates of feature points such as the center of mass can be recognized accurately.

scholarly journals Motion Detection Based on Optical Flow and Self-adaptive Threshold Segmentation

2011 ◽  
Vol 15 ◽  
pp. 3471-3476 ◽  
Author(s):  
Shui-gen Wei ◽  
Lei Yang ◽  
Zhen Chen ◽  
Zhen-feng Liu
Keyword(s):  
Optical Flow ◽  
Motion Detection ◽  
Adaptive Threshold ◽  
Threshold Segmentation ◽  
Self Adaptive

scholarly journals Robust Analysis and Laser Stripe Center Extraction for Rail Images

2021 ◽  
Vol 11 (5) ◽  
pp. 2038
Author(s):  
Huiping Gao ◽  
Guili Xu
Keyword(s):  
Center Of Mass ◽  
Adaptive Threshold ◽  
Experimental Results ◽  
Threshold Segmentation ◽  
Robust Analysis ◽  
Brightness Enhancement ◽  
Laser Stripe ◽  
Speed Up ◽  
Novel Method

In this paper, a novel method for the effective extraction of the light stripes in rail images is proposed. First, a preprocessing procedure that includes self-adaptive threshold segmentation and brightness enhancement is adopted to improve the quality of the rail image. Secondly, center of mass is utilized to detect the center point of each row of the image. Then, to speed up the procedure of centerline optimization, the detected center-points are segmented into several parts based on the geometry of the rail profile. Finally, piecewise fitting is adopted to obtain a smooth and robust centerline. The performance of this method is analyzed in detail, and experimental results show that the proposed method works well for rail images.

Advanced lane detection technique for structural highway based on computer vision algorithm

2020 ◽  
Author(s):  
K. Dinakaran ◽  
A. Stephen Sagayaraj ◽  
S.K. Kabilesh ◽  
T. Mani ◽  
A. Anandkumar ◽  
...  
Keyword(s):  
Computer Vision ◽  
Lane Detection ◽  
Detection Technique ◽  
Vision Algorithm

Research on Cloud Computing Modeling Based on Fusion Difference Method and Self-Adaptive Threshold Segmentation

2018 ◽  
Vol 32 (06) ◽  
pp. 1859010 ◽  
Author(s):  
Hong Sun ◽  
Shi-Ping Chen ◽  
Li-Ping Xu
Keyword(s):  
Difference Method ◽  
Gaussian Mixture ◽  
Adaptive Threshold ◽  
Background Model ◽  
Moving Target ◽  
Target Area ◽  
Threshold Segmentation ◽  
Update Rate ◽  
The Difference ◽  
Background Area

The traditional Gaussian mixture background model failed to build a reasonable background in complex scenarios, so this paper proposes an improved self-adaptive Gaussian mixture background modeling which integrates the difference method and adaptive threshold segmentation to improve the traditional one. In the proposed model, the difference method is applied to achieve the segmentation of changing area and background area, and different weight update policies are used for different areas. Background area updates background model with a fixed update rate. The changing region is divided into moving target area and background show area with the fusion of adaptive threshold; the background show area has a large update rate, allowing the previously obscured parts to recover rapidly; the moving target area won’t build new Gaussian components for the Gaussian mixture model. Experiments show that the video sequence algorithm with uncertainties of building background model has good adaptability. It helps to improve computing speed to a large extent and it can also respond to the change of the actual scene quickly.

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