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基于動態(tài)圖像閾值的智能車輛路徑導(dǎo)航
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國家自然科學(xué)基金資助項目（51075112）、安徽科技學(xué)院人才引進(jìn)（穩(wěn)定）資助項目（ZRC2011302）和安徽高校省級自然科學(xué)研究資助項目(KJ2013B074)


Path Tracking of Intelligent Vehicle Based on Dynamic Image Threshold
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    摘要:

    使用機器視覺技術(shù)進(jìn)行智能車輛車道路徑識別時，其識別效果易受光照等外界因素的影響?？紤]到條帶狀的導(dǎo)航路徑在獲取的路徑圖像中的寬度應(yīng)該在一個固定范圍內(nèi)，可以根據(jù)使用某一圖像閾值識別路徑后該路徑的橫向?qū)挾扰卸ㄏ惹笆褂玫拈撝凳欠襁m合，并進(jìn)行相應(yīng)調(diào)整，從而獲取到適合各種環(huán)境的動態(tài)閾值。在給出動態(tài)圖像閾值的獲取流程及實現(xiàn)方法的基礎(chǔ)上，對智能車輛車道路徑識別和跟蹤系統(tǒng)進(jìn)行了軟硬件設(shè)計，并進(jìn)行實車道路試驗。試驗結(jié)果表明，與一般最優(yōu)閾值算法相比，提出的動態(tài)閾值方法能夠在各種光照條件下，尤其是強光照下準(zhǔn)確地識別導(dǎo)航路徑，且路徑跟蹤具有較好的精確性和魯棒性。

    Abstract:

    The path recognition for vision-guided intelligent vehicle is easily affected by environmental conditions such as illumination. Considering the width of the path in the captured image should be in a fixed range, the recognized path width could be used to determine whether the previously-used threshold was suitable or not. And then the threshold could be adjusted to a suitable value to recognize the path accurately. The process and method for acquiring the dynamic image threshold was presented, and the path recognition and tracking system was designed. The experiments showed the dynamic image threshold could recognize the path more efficiently than other common optimal threshold algorithm under different conditions, especially under strong illumination, and the intelligent vehicle can track the path accurately and robustly.

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李進(jìn),陳杰平,徐朝勝,汪明磊,王家恩.基于動態(tài)圖像閾值的智能車輛路徑導(dǎo)航[J].農(nóng)業(yè)機械學(xué)報,2013,44(4):39-44. Li Jin, Chen Jieping, Xu Chaosheng, Wang Minglei, Wang Jiaen. Path Tracking of Intelligent Vehicle Based on Dynamic Image Threshold[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(4):39-44.

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  • 在線發(fā)布日期: 2013-03-28
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