基于全自动泊车与对数变换法的轨迹图像边缘信息细节化检测
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内蒙古科技大学 工程训练中心,北京中铁建电气化设计研究院

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TP391.41

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内蒙古科技大学创新基金(2015QDL22)


Edge Detection of Track and Image Based on Automatic Parking
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Inner Mongolia University of Science and Technology Engineering Training Center,(Beijing) China Railway Construction Electrification Design&Research Institute

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    摘要:

    为解决传统边缘检测方法中阈值设置过高或过低,致使关键信息被遗漏或干扰信息被误看作重要信息,造成边缘检测结果不可靠的问题。通过引入自适应阈值思想,研究了基于全自动泊车的轨迹图像边缘检测方法。对采集的全自动泊车的轨迹图像进行直方图均衡化和自适应二值化处理,以及先腐蚀后膨胀的操作,对小对象物体及平滑较大物体边界进行消除。通过一阶微分算子求解经预处理后图像不同点的梯度幅值与梯度方向,细化梯度幅值图像中的屋脊带,仅保留幅值的局部极大值。采用对数变换法对梯度范围进行扩展。通过新的局部自适应阈值化方法确定阈值,实现全自动泊车轨迹图像边缘的初检测。针对轨迹图像边缘直线线段,选用Hough变换法提取其中的直线特征,获取直线轨迹。结果表明,所提方法边缘检测细节化好,可见整体性能优。

    Abstract:

    In order to solve the problem that the threshold is too high or too low in the traditional edge detection method, the key information is omitted or the interference information is mistaken as important information, resulting in unreliable edge detection results. By introducing the idea of adaptive threshold, this paper studies the edge detection method of trajectory image based on automatic parking. Histogram equalization, adaptive binarization and corrosion followed by expansion are used to eliminate small objects and smooth large objects. The gradient amplitude and gradient direction of different points in the pre-processed image are solved by first-order differential operator, and the ridge band in the gradient amplitude image is refined, only the local maximum of the amplitude is preserved. The logarithmic transformation method is used to expand the gradient range. A new local adaptive thresholding method is used to determine the thresholds and realize the automatic edge detection of parking track images. Hough transform is used to extract the straight line feature of the edge line segment of the trajectory image to obtain the straight line trajectory. The results show that the edge detection method is detailed and the overall performance is excellent.

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引用本文

李瑾泽,乔桢. 基于全自动泊车与对数变换法的轨迹图像边缘信息细节化检测[J]. 科学技术与工程, 2019, 19(2): .
LI Jinze, QIAO zhen. Edge Detection of Track and Image Based on Automatic Parking[J]. Science Technology and Engineering,2019,19(2).

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历史
  • 收稿日期:2018-09-07
  • 最后修改日期:2018-11-06
  • 录用日期:2018-11-09
  • 在线发布日期: 2019-01-23
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