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Algorithm for unmanned aerial vehicle aerial different-source image matching 期刊论文
Optical Engineering, 2016, 卷号: 55, 期号: 12
作者:  Zuo, Y. J.;  J. H. Liu;  M. Y. Yang;  X. Wang and M. C. Sun
收藏  |  浏览/下载:17/0  |  提交时间:2017/09/11
智能视频监控系统中若干关键技术研究 学位论文
博士: 中国科学院大学, 2015
作者:  毕国玲
收藏  |  浏览/下载:160/0  |  提交时间:2015/11/30
Rotation invariant feature lines transform for image matching 期刊论文
Journal of Electronic Imaging, 2014, 卷号: 23, 期号: 5, 页码: 10
Zhang Y.; Qu H. S.
收藏  |  浏览/下载:16/0  |  提交时间:2015/04/24
Recognition technology of large-scale hybrid-distortion target 期刊论文
Guangzi Xuebao/Acta Photonica Sinica, 2014, 卷号: 43, 期号: 9
Ren B.; Ma J.; Lan L.; Wang W.-S.
收藏  |  浏览/下载:12/0  |  提交时间:2015/04/24
Rotation and scaling invariant feature lines for image matching (EI CONFERENCE) 会议论文
2011 International Conference on Mechatronic Science, Electric Engineering and Computer, MEC 2011, August 19, 2011 - August 22, 2011, Jilin, China
Zhang Y.; Wang Y.; Qu H.
收藏  |  浏览/下载:15/0  |  提交时间:2013/03/25
Image matching has been one of the most fundamental issues computer vision over the decades. In this paper we propose a novel method based on making use of feature lines in order to achieve more robust image matching. The feature lines have the properties of rotation and scaling invariance  coined RIFLT(Rotation invariant feature line transform). Experimental results demonstrate the effectiveness and efficiency of the proposed method. Compare with the famous powerful algorithm Scale Invariant Feature Transform(SIFT)  the proposed method is more insensitive to noise. And for certain sequence of images  which contain clear lines  the proposed method is more efficiency. Using the feature lines obtained by our method  it is possible to matching two scene images with different rotation angles  scale and light distort. 2011 IEEE.  
Scene matching based on directional keylines and polar transform (EI CONFERENCE) 会议论文
2010 IEEE 10th International Conference on Signal Processing, ICSP2010, October 24, 2010 - October 28, 2010, Beijing, China
Zhang Y.; Qu H.; Wang Y.
收藏  |  浏览/下载:19/0  |  提交时间:2013/03/25
Scene matching under complex background is a priority and difficulty in the field of computer vision  it has the characteristics of rotation and scaling invariance  commonly used in matching real-time collected images and photos for navigation. Scene matching techniques are faced with complex natural scenes  anti-light and anti-slight-distortion  the image distortion exist  applicable for complex scene matching. The project has a new idea: combining the keylines with the vectors description based on polar image translation  such as light  and utilize the rotation-scale-invariance vectors to describe the extracted keylines  change of gray levels  this method includes three steps: keylines extraction  perspective  description and matching. Preliminary experiments show that this keylines-based scene matching algorithm is applicable for image matching under complex background. 2010 IEEE.  scaling and other differences  which cause matching difficult. This paper aims to find a scene matching algorithm  
Target track system design based on circular projection (EI CONFERENCE) 会议论文
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
Song H.-J.; Zhu M.; Hu S.; Shen M.-L.
收藏  |  浏览/下载:14/0  |  提交时间:2013/03/25
Template matching is the process of searching the present and the location of a reference image or an object in a scene image. Template matching is a classical problem in a scene analysis: given a reference image of an object  decide whether that object exists in a scene image under analysis  and find its location if it does. The template matching process involves cross-correlating the template with the scene image and computing a measure of similarity between them to determine the displacement. The conventional matching method used the spatial cross-correlation process which is computationally expensive. Some algorithms are proposed for this speed problem  such as pyramid algorithm  but it still can't reach the real-time for bigger model image. Moreover  the cross-correlation algorithm can't be effective when the object in the image is rotated. Therefore  the conventional algorithms can't be used for practical purpose. In this paper  an algorithm for a rotation invariant template matching method based on different value circular projection target tracking algorithm is proposed. This algorithm projects the model image as circular and gets the radius and the sum of the same radius pixel value. The sum of the same radius pixel value is invariable for the same image and the any rotated angle image. Therefore  this algorithm has the rotation invariant property. In order to improve the matching speed and get the illumination invariance  the different value method is combined with circular projection algorithm. This method computes the different value between model image radius pixel sum and the scene image radius pixel sum so that it gets the matching result. The pyramid algorithm also is been applied in order to improve the matching speed. The high speed hardware system also is been design in order to meet the real time requirement of target tracking system. The results show that this system has the good rotate invariance and real-time property.  


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