Research on Stereo Matching Algorithm in Intelligent Vehicle Application

2014 ◽  
Vol 678 ◽  
pp. 35-38 ◽  
Author(s):  
Peng He ◽  
Feng Gao

Perception of environment in front of driving vehicle is a core investigation theme of intelligent vehicle technologies aiming to increase safety, convenience and efficiency of driving. Using stereo vision for environment perception is a hot technology. This paper developed an algorithm for stereo matching in intelligent vehicle application. The experimental results indicate that this algorithm is effective. Furthermore, this algorithm paves the way for the implementation of automotive driver assistance system.

2013 ◽  
Vol 765-767 ◽  
pp. 2229-2232
Author(s):  
Peng He ◽  
Feng Gao

Lane detection is a crucial component of automotive driver assistance system aiming to increase safety, convenience and efficiency of driving. This paper developed a vision based algorithm of detecting road lanes which is performed by extracting edges and finding straight lines using improved Hough transform. The experimental results indicate that this algorithm is effective and precise. Furthermore, this algorithm paves the way for the implementation of automotive driver assistance system.


2016 ◽  
Vol 35 (1) ◽  
pp. 39 ◽  
Author(s):  
Rostam Affendi Hamzah ◽  
Haidi Ibrahim ◽  
Anwar Hasni Abu Hassan

This paper presents a new method of pixel based stereo matching algorithm using illumination control. The state of the art algorithm for absolute difference (AD) works fast, but only precise at low texture areas. Besides, it is sensitive to radiometric distortions (i.e., contrast or brightness) and discontinuity areas. To overcome the problem, this paper proposes an algorithm that utilizes an illumination control to enhance the image quality of absolute difference (AD) matching. Thus, pixel intensities at this step are more consistent, especially at the object boundaries. Then, the gradient difference value is added to empower the reduction of the radiometric errors. The gradient characteristics are known for its robustness with regard to the radiometric errors. The experimental results demonstrate that the proposed algorithm performs much better when using a standard benchmarking dataset from the Middlebury Stereo Vision dataset. The main contribution of this work is a reduction of discontinuity errors that leads to a significant enhancement on matching quality and accuracy of disparity maps.


Author(s):  
D. S. Bhargava ◽  
N. Shyam ◽  
K. Senthil Kumar ◽  
M. Wasim Raja ◽  
P Sivashankar.

2003 ◽  
Author(s):  
Shinnosuke Ishida ◽  
Jun Tanaka ◽  
Satoshi Kondo ◽  
Masahito Shingyoji

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