本文選題：靠岸艦船檢測 + 港口定位�。� 參考：《華中科技大學(xué)學(xué)報(bào)(自然科學(xué)版)》2017年10期

【摘要】：針對(duì)可見光圖像中靠岸艦船的灰度、紋理等特征的自動(dòng)檢測比較困難的問題,提出一種基于港口匹配和海域分割的靠岸艦船檢測方法.根據(jù)飛行器實(shí)時(shí)返回的姿態(tài)信息,將港口模板變換到實(shí)時(shí)圖同一視角下進(jìn)行港口配準(zhǔn),確定實(shí)時(shí)圖海域部分,再對(duì)海域進(jìn)行分割,檢測出艦船.采用基于邊緣梯度矢量的港口配準(zhǔn)方法,克服岸內(nèi)邊緣干擾,提高匹配精度.提出一種特征融合聚類結(jié)合生長的分割算法,解決灰度不均勻?qū)е碌姆指詈笈灤瑪嗔熏F(xiàn)象,優(yōu)化海陸分割效果.試驗(yàn)結(jié)果證明了該方法的有效性和魯棒性.
[Abstract]:Aiming at the difficulty of automatic detection of landing ship's gray and texture features in visible light image, a method based on port matching and sea area segmentation is proposed. According to the attitude information returned by the aircraft in real time, the port template is transformed to the same angle of view of the real-time image for port registration, and the real-time sea area is determined, then the sea area is segmented, and the ship is detected. The port registration method based on edge gradient vector is used to overcome the inshore edge interference and improve the matching accuracy. A feature fusion clustering combined with growing segmentation algorithm is proposed to solve the ship fracture phenomenon caused by uneven grayscale and to optimize the effect of sea-land segmentation. The experimental results show that the method is effective and robust.
【作者單位】： 華中科技大學(xué)自動(dòng)化學(xué)院;華中科技大學(xué)多譜信息處理技術(shù)國家重點(diǎn)實(shí)驗(yàn)室;北京航天自動(dòng)控制研究所;
【基金】：國家十三五科技預(yù)研資助項(xiàng)目(41415020402)
【分類號(hào)】：TP751;U675.79
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本文編號(hào)：1978494