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Improved Target Signal Source Tracking and Extraction Method Based on Outdoor Visible Light Communication Using a Cam-Shift Algorithm and Kalman Filter

机译:改进的基于Cam-Shift算法和卡尔曼滤波的室外可见光通信目标信号源跟踪提取方法

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摘要

An improved Cam-Shift algorithm with a Kalman filter applied to image-sensor based on outdoor visible light communication (OVLC) is presented in this paper. The proposed optimized tracking algorithm is used to track and extract the region of the target signal source Light Emitting Diode (LED) that carries modulated information for data transmission. Extracting the target signal source LED area is the premise of an image-sensor-based VLC system, especially in outdoor dynamic scenes. However, most of the existing VLC studies focus on data transmission rate, visible light positioning, etc. While the actual first step of realizing communication is usually ignored in the field of VLC, especially when the transmitter (signal source LED) or the receiver (image sensor) is moving in a more complex outdoor environment. Therefore, an improved tracking algorithm is proposed in this paper, aiming at solving the problem of extracting the region of the target signal source LED accurately in dynamic scenes with different interferences so as to promote the feasibility of VLC applications in outdoor scenes. The proposed algorithm considers color characteristics and special distribution characteristics of the moving target at the same time. The image is converted to a color probability distribution map based on the color histogram of the target and adaptively adjusts the location and size of the search window based on the results obtained from the previous frame. Meanwhile, it predicts the motion state of the target in the next frame according to the position and velocity information of the current frame to enhance accuracy and robustness of tracking. Experimental results show that the tracking error of the proposed algorithm is 0.85 cm and the computational time of processing one frame is 0.042 s. Besides, results also show that the improved algorithm can track and extract the target signal source LED area completely and accurately in an environment of many interference factors. This study confirms that the proposed algorithm can be applied to an OVLC system with many interferences to realize the actual first step of communication in an image-sensor-based VLC system, laying foundations for subsequent data transmission and other steps.
机译:提出了一种改进的基于卡尔曼滤波的Cam-Shift算法,该算法基于室外可见光通信(OVLC)应用于图像传感器。提出的优化跟踪算法用于跟踪和提取目标信号源发光二极管(LED)的区域,该区域承载调制信息以进行数据传输。提取目标信号源LED区域是基于图像传感器的VLC系统的前提,尤其是在室外动态场景中。但是,大多数现有的VLC研究都集中在数据传输速率,可见光定位等方面。尽管在VLC领域中通常忽略实现通信的实际第一步,尤其是在发射机(信号源LED)或接收机(图像传感器)正在更复杂的室外环境中移动。因此,本文提出一种改进的跟踪算法,以解决在具有不同干扰的动态场景中准确提取目标信号源LED区域的问题,从而提高VLC在室外场景中的可行性。该算法同时考虑了运动目标的颜色特征和特殊分布特征。图像根据目标的颜色直方图转换为颜色概率分布图,并根据从前一帧获得的结果自适应地调整搜索窗口的位置和大小。同时,它根据当前帧的位置和速度信息预测下一帧目标的运动状态,从而提高跟踪的准确性和鲁棒性。实验结果表明,该算法的跟踪误差为0.85 cm,处理一帧的计算时间为0.042 s。此外,结果还表明,该改进算法能够在多种干扰因素的环境下,完整,准确地跟踪和提取目标信号源LED区域。这项研究证实了所提出的算法可以应用于具有很多干扰的OVLC系统,以实现基于图像传感器的VLC系统中通信的实际第一步,为后续的数据传输和其他步骤奠定基础。

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