引用本文:章海兵,刘士荣,张波涛.H-S直方图反向投影结合特征点提取的双目视觉定位算法[J].控制理论与应用,2014,31(5):614~623.[点击复制]
ZHANG Hai-bing,LIU Shi-rong,Zhang Bo-tao.Binocular vision position algorithm using hue-saturation histogram back-project combined with feature point extraction[J].Control Theory and Technology,2014,31(5):614~623.[点击复制]
H-S直方图反向投影结合特征点提取的双目视觉定位算法
Binocular vision position algorithm using hue-saturation histogram back-project combined with feature point extraction
摘要点击 3770  全文点击 2432  投稿时间:2013-07-06  修订日期:2014-01-24
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DOI编号  10.7641/CTA.2014.30679
  2014,31(5):614-623
中文关键词  双目视觉  目标定位  立体校正  反向投影  SURF算法  特征提取
英文关键词  binocular vision  object position  stereo rectification  back-projection  SURF algorithm  feature extraction
基金项目  国家自然科学基金资助项目(61175093).
作者单位E-mail
章海兵 杭州电子科技大学 电气自动化研究所
检测仪表与自动化系统集成技术教育部工程研究中心 
 
刘士荣* 杭州电子科技大学 电气自动化研究所
检测仪表与自动化系统集成技术教育部工程研究中心 
liushirong@hdu.edu.cn 
张波涛 杭州电子科技大学 电气自动化研究所
检测仪表与自动化系统集成技术教育部工程研究中心 
 
中文摘要
      低成本双目视觉系统通常采用价格低廉的非测量相机, 其视觉定位精度较低. 若需获得较高的视觉定位精 度,可通过算法来弥补或减少定位误差.本文阐述了基于H--S(hue-saturation)直方图反向投影结合特征点提取的双 目视觉定位算法, 可提取左右摄像头图像特征点, 并用左图特征点和极线约束对右图特征点进行修正, 从而可实现 双目视觉定位. 在此基础上, 为了进一步提高定位精度和减少计算量, 采用了快速鲁棒性特征(SURF)算法提取左右 图像的兴趣点, 并利用间接立体匹配法改进了右图特征点提取. 实验结果表明, 在低成本视觉定位系统中采用该算 法可以有效地提高定位精度.
英文摘要
      In low-cost binocular vision system, an inexpensive non-measure camera usually results in a low visual positioning accuracy. To obtain higher visual positioning accuracy, there exist some algorithms to reduce or compensate positioning errors. A binocular vision positioning algorithm based on H–S (hue-saturation) histogram back-projection combined with feature point extraction is proposed in this paper. In this algorithm, the H–S histogram back-projection method is employed to extract the feature points of images from the left and the right cameras; and then, the feature points of the left image and the epipolar constraints are employed to correct the feature points of the right image, to achieve binocular vision positioning. In order to further improve the positioning accuracy and reduce the cost of computation, the SURF (speed up robust feature) algorithm is used to extract the interest points of both left and right images, and an indirect stereo matching approach is employed to improve the feature point extraction of the right image. Experiment results show that for the low-cost visual positioning system this algorithm can effectively improve the positioning accuracy.