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Motion Multi-object Detection Method under Complex Environment

机译:复杂环境下的运动多物体检测方法

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摘要

An optimization object detection method based on color image symmetrical frame-difference is proposed in order to solve the problem of motion multi-object detection difficult under complex environment. In this paper, firstly the color images distance is defined to calculate the frame-difference between two adjacent images. Then the before and after symmetrical image-distance of three adjacent images in difference frame interval step can be completed respectively. Secondly, an optimization binary method is designed to extract more object pixels. And the before and after object binary results of the adjacent images with the same middle (key frame) image are given respectively. At last, motion multi-object of the key frame image is achieved by the fusion result of logical AND between the before and after object binary results depending on three-frame-adjacent images with the same key frame. Actual color images from traffic surveillance system are used to test, the experimental result shows that the optimization object detection algorithm based on symmetrical frame difference in the proper step can extract motion multi-objects in different movement speed under complex environment and its accuracy and effectiveness of the proposed algorithm are verified.
机译:提出了一种基于彩色图像对称帧差异的优化对象检测方法,以解决复杂环境下的运动多物体检测问题。在本文中,首先定义彩色图像距离以计算两个相邻图像之间的帧差。然后可以分别完成三个相邻图像的三个相邻图像的对称图像距离的前后和之后。其次,设计优化二进制方法以提取更多对象像素。并且分别给出具有相同中间(关键帧)图像的相邻图像的对象二进制结果。最后,通过逻辑的融合结果以及在对象二进制结果之前和之后的融合结果,根据具有相同密钥帧的三帧相邻的图像来实现逻辑帧图像的融合结果。来自流量监控系统的实际彩色图像用于测试,实验结果表明,基于适当步骤中的基于对称帧差的优化对象检测算法可以在复杂环境下提取不同运动速度的运动多象及其精度和效率验证了所提出的算法。

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