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基于線(xiàn)結構光的亞像素精度焊縫提取方法研究
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長(cháng)江大學(xué) 油氣資源與勘探技術(shù)教育部重點(diǎn)實(shí)驗室

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Sub-pixel precision seam extraction method based on line structured light
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    摘要:

    對于激光視覺(jué)焊縫跟蹤系統,基于線(xiàn)性結構光快速、高精度地提取焊縫特征點(diǎn)是系統搭建的關(guān)鍵。現有算法多是采取像素級別的提取特征,現提出改進(jìn)的亞像素精度算法用以提取焊縫特征點(diǎn)。與以往算法不同的是,算法不需要進(jìn)行閾值的選取,提取條紋中心線(xiàn)和檢測特征點(diǎn)的過(guò)程,都采用了先計算出亞像素位置,再對圖像進(jìn)行處理,顯著(zhù)地提高了算法的精度。并且目前圖像處理多采用深度學(xué)習,但都為對像素的離散點(diǎn)實(shí)現,難以做到亞像素精度。實(shí)驗結果表明,該算法能夠滿(mǎn)足生產(chǎn)實(shí)際要求,能夠實(shí)時(shí)、精確地實(shí)現焊縫提取。

    Abstract:

    For the laser vision seam tracking system, it is the key to extract the weld feature points quickly and accurately based on the linear structured light. Most of the existing algorithms are pixel-level feature extraction. Now an improved sub-pixel accuracy algorithm is proposed to extract weld feature points. Different from the previous algorithm, the algorithm does not need to select the threshold value. In the process of extracting the fringe centerline and detecting the feature points, the sub-pixel position was calculated first, and then the image was processed. The accuracy of the algorithm was greatly improved. Moreover, image processing mostly adopts deep learning technology at present. But the deep learning technology is all for the realization of pixel discrete point, it is difficult to achieve sub-pixel precision. The experimental results showed that the algorithm could meet the actual production requirements, and could achieve real-time and accurate weld extraction.

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胡韻松,王軍民,付嘉瑋,李雄軍,劉威.基于線(xiàn)結構光的亞像素精度焊縫提取方法研究計算機測量與控制[J].,2020,28(7):162-166.

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歷史
  • 收稿日期:2019-11-21
  • 最后修改日期:2019-12-11
  • 錄用日期:2019-12-12
  • 在線(xiàn)發(fā)布日期: 2020-07-14
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