李斌, 孙华峰. 内河运动船舶的准确检测跟踪技术研究[J]. 微电子学与计算机, 2012, 29(11): 180-184.
引用本文: 李斌, 孙华峰. 内河运动船舶的准确检测跟踪技术研究[J]. 微电子学与计算机, 2012, 29(11): 180-184.
LI Bin, SUN Hua-feng. Research the Inland River Motion Ships Accurately Detection and Tracking Algorithm[J]. Microelectronics & Computer, 2012, 29(11): 180-184.
Citation: LI Bin, SUN Hua-feng. Research the Inland River Motion Ships Accurately Detection and Tracking Algorithm[J]. Microelectronics & Computer, 2012, 29(11): 180-184.

内河运动船舶的准确检测跟踪技术研究

Research the Inland River Motion Ships Accurately Detection and Tracking Algorithm

  • 摘要: 研究内河航运中运动船舶的准确检测跟踪.利用采集的红外视频图像进行船跟踪时,由于船舶的红外图像轮廓、形状和纹理特征不清晰,其用于目标描述的灰度特征不明显,传统的单一灰度特征检测跟踪方法不能有效描述灰度特征不明显的船舶目标,造成船舶检测跟踪的准确度不高的问题.为此,提出特征融合的船舶检测跟踪方法.将船舶的灰度特征和运动特征融合来描述运动船舶目标,避免传统单一灰度特征方法不能有效描述特征不明显的船舶目标问题,并利用粒子滤波算法构建观测概率模型,完成运动船舶的检测跟踪.实验表明,特征融合的方法能够有效描述船舶运动目标,准确完成船舶的检测跟踪,取得了理想的结果.

     

    Abstract: Research in motion of inland water transport ship accurately detection of tracking.Using the infrared video image collection tracking the ship from the ship image,the infrared images of contour shape and texture features are not clear,gray characteristicsused used to describe the goal is not obvious.The traditiona single gray feature detection and tracking method does not effectively describe ship goals of gray characteristics not obvious,causiong the ship detection and tracking accuracy is not high.In order to solve this problem,this paper put forward the fusion feature detection and tracking of ship method.Combine the ship of gray characteristics and movement characteristics fusion to describe movement ship goals,avoiding the traditional single gray characteristics method does not describe effectively characteristics of not obvious ship target.And by using particle filter algorithm construct observation probability model,complete the movement of the ship detection and tracking.Experiments show that features fusion method can describe effectively ship moving targets,accurate detection and tracking of the complete ship,ideal result was obtained.

     

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