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基于DLT的双目视觉火源图像立体匹配新算法

New Algorithm of Binocular Vision Fire Image Stereo Maching Based on DLT
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摘要 为了提高双目视觉过程中对火源图像立体匹配的准确性和匹配速度,提出基于DLT的双目视觉火源图像立体匹配新算法。首先用直接线性变换DLT算法对火源图像进行图像校正,其次用Harris算法对其进行特征点提取,最后利用SURF算法对提取的特征点进行特征向量及特征向量在多维空间中对应点之间的欧式距离进行计算,得到两个特征点的相似程度并给予正确匹配结果。实验结果表明,该算法提高了火源图像立体匹配的准确性和匹配速度,适用于大空间建筑双目视觉火灾自动定位系统,具有一定的应用价值。 In order to improve the accuracy and the matching speed of fire image stereo matching in the process of binocular vision.The new algorithm of binocular vision fire image stereo maching based on DLT is proposed in this paper.Fristly,using direct linear transformation DLT algorithm correct the fire image.Secondly using Harris algorithm extract the feature points.Fi- nally,using SURF calculate the euclidean distance between corresponding points of feature vectors in the multidimensional space,getting the degree of similarity of two points and making the correct matching result.
出处 《工业控制计算机》 2014年第7期124-126,共3页 Industrial Control Computer
基金 教育部高等学校博士学科点专项科研基金(20126120110008) 陕西省教育厅产业化项目(2011JG12) 陕西省自然科学基础研究计划项目(2012JQ8021) 教育厅专项科研项目(2013JK1144)
关键词 双目视觉 火源图像 立体匹配 DLT HARRIS SURF binocular vision,fire image,stereo matching,DLT Harris SURF
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  • 1刘宇斌.一种分阶段的高精度亚像素特征点提取方法[J].南华大学学报(自然科学版),2006,20(2):54-57. 被引量:6
  • 2C.G.Harris, M.J.Stephens. A combined comer and edge detector[A].In:Proceedings Fourth Alvey Vision Conference[C].Manchester,U.K., 1988:147-151.
  • 3Schmid C, Mohr R, Bauckhage C. Evaluation of Interest Point Detectors [J].International 3ournal of Computer Vision, 2000,37(2) : 151-172.
  • 4J.A.Noble. Finding corners [J].Image and Vision Computing, 1988,6(2) : 121-128.
  • 5SCHMID C, MOHR R, BAUCKHAGE C. Evaluation of interest point detectors [J]. Int J Comput Vision, 2000, 37(2): 151-172.
  • 6LOWED G. Distinctive image features from seale-invariant keypoints [J]. Int J Comput Vision, 2004, 60(2) : 91-110.
  • 7MIKOLAJCZYK K, SCHMID C. A performance evaluation of local descriptors [J[. IEEE Trans Pattern Anal Maeh Intell, 2005, 27(10): 1615-1630.
  • 8BASTANI.AR Y, TEMIZEL A, YARDIMCI Y. Improved SIFT matching for image pairs with scale difference [J]. Electron Lett, 2010, 46(5): 346-348.
  • 9YAN K, SUKTHANKAR R. PCA-SIFT: a more distinctive representation for local image descriptors [-C]// Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattren Recognition. Wash- ington, DC, USA: IEEE, 2004, 2: 506-513.
  • 10DELPONTE E, ISGRO F, ODONE F, et al. SVD-matching using SIFT features [J]. Graph Models, 2006, 68(5/6) : 415-431.

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