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提高激光测头测量精度的图像优化方法 被引量:1

Improvement on measurement precision of laser probe using image optimization method
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摘要 由于激光测头的测量精度主要依赖于图像处理模块,因此为提高测量精度,首先提出基于图像反馈的自适应激光亮度调节方法,设计1个激光亮度控制器,并对不同激光强度下拍摄的图像进行激光条纹中心点提取,以选择最合适的激光强度;然后应用离散的Gabor滤波模板对激光条纹进行增强处理,以提高测量条纹的连续性.实验表明:(1)自适应激光亮度调节方法与采用手动调节方法选取的最佳激光亮度偏差不超过5级,其有效性较高;(2)改进后的激光测头从扫描数据的均匀程度到连续性都远好于改进前的测头.该方法对测量精度的提高较大,为其在复杂型面测量领域的应用打下良好基础. The measurement precision of laser probe mainly depends on the image process model. To improve the measurement precision, a method is proposed based on image feedback, an adaptive laser brightness adjustment controller is designed, and the central points of laser stripe images that are shot are extracted to select the most appropriate laser brightness. The discrete Gabor filter template is used to enhance the image process of laser stripe to improve the continuity of measurement stripe. The experiments indicate: (1)the best laser brightness obtained by the method of adaptive laser brightness adjustment is not more than 5 degree compared with that obtained by manual adjustment, and its validity is improved; (2) as to the uniformity or continuity of the scanned data, the improved laser probe is far better than the normal one. The method can improve the measurement precision and lay a sound basis for its application on the measurement of complex surfaces.
出处 《计算机辅助工程》 2008年第3期81-83,共3页 Computer Aided Engineering
基金 国家自然科学基金(50575029) 大连海事大学青年科研基金(DLMU-ZL-200717)
关键词 激光测头 图像处理 自适应激光亮度调节 GABOR滤波器 laser probe image process adaptive laser brightness adjustment Gabor filter
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  • 1MA Zi, HU Ying, HUANG Jin, et al. A novel design of in pipe robot for inner surface inspection of large size pipes[J]. Int J Mech Based Des Struct & Machines, 2007, 35 (4) : 447-466.
  • 2杨培,徐滨士,吴林.基于结构光三维视觉的再制造工件的测量及重建[J].焊接学报,2005,26(8):12-15. 被引量:7
  • 3李敏,林财兴,吕永.汽车内饰件的测量[J].计算机辅助工程,2004,13(1):33-38. 被引量:2
  • 4LIN Hong, WAN Yifei, JAIN A. Fingerprint image enhancement: algorithm and performance evaluation [ J]. IEEE Trans Pattern Anal & Machine Intelligence, 1998, 20(8): 777-789.

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