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面向散斑紋理圖像的相機聚焦評價(jià)算法
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北京機械設備研究所

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Camera Focus Evaluation Algorithm for Speckle Texture Image
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    摘要:

    針對光學(xué)測量中操作員依照經(jīng)驗調節相機焦距而導致測量結果歧義這一問(wèn)題進(jìn)行研究,解決傳統相機聚焦方法在散斑紋理圖像上不適用的缺陷,基于灰度共生矩陣的熵、慣性矩和相關(guān)性三種特征量,提出一種面向散斑紋理圖像的相機自動(dòng)聚焦算法,輔助操作員調節相機。通過(guò)不同實(shí)驗環(huán)境下采集的散斑紋理圖像,驗證所提算法單峰性和無(wú)偏性的特點(diǎn),且具有一定抗噪能力。相比于傳統評價(jià)算法,本文所提算法對散斑紋理圖像的判斷具有更強的針對性和更好的適用性,可為后續的精確測量提供保障。

    Abstract:

    Aiming at the ambiguity of measurement results caused by the operator adjusting the camera focal length according to experience in optical measurement, and solving the defect that the traditional camera focusing approaches could not applicable to speckle texture image, a camera automatic focusing algorithm for speckle texture image is proposed based on the entropy, moment of inertia and correlation of gray level co-occurrence matrix., which could assist the operator in adjusting the camera. The speckle texture images collected in different experimental environments verity that the proposed algorithm has the characteristics of unimodal and unbiased hardware, and has certain anti-noise ability. Compared with the traditional evaluation algorithm, the proposed algorithm has stronger pertinence and better applicability to the judgment of speckle texture image, and can provide guarantee for subsequent accurate measurement.

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苑文楠,賈彥翔,蔣大偉,歐陽(yáng)銅,雷春,邱旭陽(yáng).面向散斑紋理圖像的相機聚焦評價(jià)算法計算機測量與控制[J].,2022,30(4):244-248.

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歷史
  • 收稿日期:2021-10-18
  • 最后修改日期:2021-11-23
  • 錄用日期:2021-11-24
  • 在線(xiàn)發(fā)布日期: 2022-04-21
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