融合分数阶微分边缘特征的自适应跟踪
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摘要
为提高跟踪方法对背景信息、光照变化的抗干扰能力,提出融合分数阶微分边缘特征信息的改进跟踪方法。将RL分数阶微分边缘检测算子与Laplacian边缘检测算子进行融合,构造出对高、中频信息提升,而对低频信息能够非线性保留的混合边缘检测算子,并利用其实现目标模板及场景图像的边缘特征信息检测。基于目标色度特征和边缘特征两种直方图模型,分别建立场景图像的反向概率投影值,根据背景信息的动态变化,以抑制背景干扰信息为目的,建立自适应融合的反向概率投影图,提高算法对不确定环境变化信息的鲁棒性。实验结果表明,混合边缘检测算子能够提高边缘图像的信噪比,改善边缘提取的效果。边缘、色度特征信息自适应融合的跟踪方法单帧跟踪时间小于20ms,满足实时性要求。该方法能够在光照变化明显和与目标颜色相似背景等情况下有效实现目标识别与跟踪功能。
To enhance the anti-jamming ability with respect to the background and the illumination variation,an improved tracking method based on the fractional differential edge feature was proposed.The R-L fractional differential edge detection operator and Laplacian edge detection operator were fused to construct a hybrid edge detection operator that could enhance the high and middle frequency information and hold the low frequency information nonlinearly.The hybrid edge detection operator was used to detect the edge information of the target template and the tracking scene.The hue histogram and edge histogram of the target were separately modeled.According to the dynamic information of the background,the back-projection image could be modeled by adaptively fusing the back-projec-tion probability values,which can be separately obtained based on the two histograms to suppress the interfering information from the background.Experiments show that the hybrid edge detection operator can enhance the signal-to-noise ratio of the edge image and improve the quality of the edge image.Furthermore,the tracking time of the tracking method based on the adaptive fusion of the edge feature and hue feature is less than 20 ms,which can meet the real-time requirements of tracking systems.The tracking method can be applied to effectively track the target in an environment with varying illumination in a background similar to the target.
To enhance the anti-jamming ability with respect to the background and the illumination variation,an improved tracking method based on the fractional differential edge feature was proposed.The R-L fractional differential edge detection operator and Laplacian edge detection operator were fused to construct a hybrid edge detection operator that could enhance the high and middle frequency information and hold the low frequency information nonlinearly.The hybrid edge detection operator was used to detect the edge information of the target template and the tracking scene.The hue histogram and edge histogram of the target were separately modeled.According to the dynamic information of the background,the back-projection image could be modeled by adaptively fusing the back-projec-tion probability values,which can be separately obtained based on the two histograms to suppress the interfering information from the background.Experiments show that the hybrid edge detection operator can enhance the signal-to-noise ratio of the edge image and improve the quality of the edge image.Furthermore,the tracking time of the tracking method based on the adaptive fusion of the edge feature and hue feature is less than 20 ms,which can meet the real-time requirements of tracking systems.The tracking method can be applied to effectively track the target in an environment with varying illumination in a background similar to the target.
引文
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[18]王爱丽,董宝田,武鸿源,等.基于联合特征直方图的均值漂移目标跟踪算法[J].控制与决策,2016,31(10):1845-1852.WANG A L,DONG B T,WU H Y,et al..Meanshift target tracking algorithm based on joint feature histogram[J].Control and Decision,2016,31(10):1845-1852.(in Chinese)
[19]覃跃虎,支琤,徐奕.基于三维直方图的改进Camshift目标跟踪算法[J].现代电子技术,2014,37(2):29-33+37.QIN Y H,ZHI C,XU Y.Improved Camshift object tracking algorithm based on three-dimensional histogram[J]. Modern Electronic Technique,2014,37(2):29-33+37.(in Chinese)
[20]修春波,魏世安,万蓉凤.二维联合特征模型的自适应均值漂移目标跟踪[J].光电子·激光,2015,26(2):342-351.XIU C B,WEI S A,WAN R F.Camshift target tracking based on two dimension joint characteristics[J].Journal of Photoelectronics Laser,2015,26(2):342-351.(in Chinese)
[21]蒋伟,陈辉.基于分数阶微分和Sobel算子的边缘检测新模型[J].计算机工程与应用,2012,48(4):182-185.JIANG W,CHEN H.New edge detection model based on fractional differential and Sobel operator[J].Computer Engineering and Applications,2012,48(4):182-185.(in Chinese)
[2]WANG H,NGUANG S K,WEN J W.Robust video tracking algorithm:a multi-feature fusion approach[J].IET Computer Vision,2018,12(5):640-650.
[3] LUO X H,WANG F Q,LUO M L.Collaborative target tracking in lopor with multi-camera[J].Optik-International Journal for Light and Electron Optics,2016,127(23):11588-11598.
[4] SAMARJIT S,AMIT K,NAMRATA V,et al..Particle Filter With a Mode Tracker for Visual Tracking Across Illumination Changes[J].IEEE Transactions on Image Processing,2012,21(4):2340-2346.
[5] BATTIATO S,FARINELLA G M,FURNARI A,et al..An integrated system for vehicle tracking and classification[J].Expert Systems with Applications,2015,42(21):7263-7275.
[6]张雷,王延杰,孙宏海,等.采用核相关滤波器的自适应尺度目标跟踪[J].光学精密工程,2016,24(2):448-459.ZHANG L,WANG Y J,SUN H H,et al..Adaptive scale object tracking with kernelized correlation filters[J].Opt.Precision Eng.,2016,24(2):448-459.(in Chinese)
[7]王春平,王暐,刘江义,等.基于色度饱和度-角度梯度直方图特征的尺度自适应核相关滤波跟踪[J].光学精密工程,2016,24(9):2293-2301.WANG C P,WANG W,LIU J Y,et al..Scale adaptive kernelized correlation filter tracking based on HHS-OG feature[J].Opt.Precision Eng.,2016,24(9):2293-2301.(in Chinese)
[8]黄晋英,宋国浩,兰艳亭,等.交比不变的Camshift跟踪方法[J].光学精密工程,2016,24(4):945-953.HUANG J Y,SONG G H,LAN Y T,et al..Camshift tracking based on constant cross ratio[J].Opt.Precision Eng.,2016,24(4):945-953.(in Chinese)
[9]YOO H,KIM K,BYEON M,et al..Online scheme for multiple camera multiple target tracking based on multiple hypothesis tracking[J].IEEE Transactions on Circuits&Systems for Video Technology,2017,27(3):454-469.
[10] WU XY,MAO X,CHEN L J,et al..Depth image-based hand tracking in complex scene[J].Optik-International Journal for Light and Electron Optics,2015,126(20):2757-2763.
[11] LI J,CHEN H F,LI G,et al..Salient object detection based on meanshift filtering and fusion of colour information[J].IET Image Processing,2015,9(11):977-985.
[12] LI F L,ZHANG R H,YOU F.Fast pedestrian detection and dynamic tracking for intelligent vehicles within V2Vcooperative environment[J].IET Image Processing,2017,11(10):833-840.
[13]马俊凯,罗海波,常铮,等.基于可变形模型的目标跟踪算法[J].红外与激光工程,2017,46(9):292-300.MA J K,LUO H B,CHANG Z,et al..Visual tracking algorithm based on deformable parts model[J].Infrared and Laser Engineering,2017,46(9):292-300.(in Chinese)
[14] LEE R M,JEFFREY S,PETER L.A multi-dimensional hough transform-based track-before-detect technique for detecting weak targets in strong clutter backgrounds[J].IEEE Transactions on Aerospace and Electronic Systems,2011,47(4):3062-3068.
[15] DU B,SUN Y J,CAI S H,et al..Object tracking in satellite videos by fusing the kernel correlation filter and the three-frame-difference algorithm[J].IEEE Geoscience and Remote Sensing Letters,2018,15(2):168-172.
[16]林建华,刘党辉,邵显奎.多特征融合的Camshift算法及其进一步改进[J].计算机应用,2012,32(10):2814-2816.LIN J H,LIU D H,SHAO X H.Multi-feature fusion Camshift algorithm and its further improvement[J].Journal of Computer Applications,2012,32(10):2814-2816.(in Chinese)
[17]周平平,万洪林,刘慧.基于颜色和边缘特征自适应融合的人脸跟踪算法[J].中国科学技术大学学报,2017,47(10):837-842.ZHOU P P,WAN H L,LIU H.Face tracking algorithm of color and edge features based adaptive fusion[J].Journal of Science and Technology of China,2017,47(10):837-842.(in Chinese)
[18]王爱丽,董宝田,武鸿源,等.基于联合特征直方图的均值漂移目标跟踪算法[J].控制与决策,2016,31(10):1845-1852.WANG A L,DONG B T,WU H Y,et al..Meanshift target tracking algorithm based on joint feature histogram[J].Control and Decision,2016,31(10):1845-1852.(in Chinese)
[19]覃跃虎,支琤,徐奕.基于三维直方图的改进Camshift目标跟踪算法[J].现代电子技术,2014,37(2):29-33+37.QIN Y H,ZHI C,XU Y.Improved Camshift object tracking algorithm based on three-dimensional histogram[J]. Modern Electronic Technique,2014,37(2):29-33+37.(in Chinese)
[20]修春波,魏世安,万蓉凤.二维联合特征模型的自适应均值漂移目标跟踪[J].光电子·激光,2015,26(2):342-351.XIU C B,WEI S A,WAN R F.Camshift target tracking based on two dimension joint characteristics[J].Journal of Photoelectronics Laser,2015,26(2):342-351.(in Chinese)
[21]蒋伟,陈辉.基于分数阶微分和Sobel算子的边缘检测新模型[J].计算机工程与应用,2012,48(4):182-185.JIANG W,CHEN H.New edge detection model based on fractional differential and Sobel operator[J].Computer Engineering and Applications,2012,48(4):182-185.(in Chinese)