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A Tracking Method of Vanishing Point Based on Kalman Filter

A technology of trace lines and vanishing points, applied in the field of image processing, can solve problems affecting the estimation accuracy of vanishing points, and achieve the effect of reducing the impact

Active Publication Date: 2021-11-09
ZHEJIANG GONGSHANG UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In addition to the lane markings, various vehicles, shadows cast by vehicles, lane dividers and other objects often appear in the field of view observed by the cameras of the ADAS system. The intersections and lanes formed by the straight lines determined by the edges of these objects There is usually a large deviation in the vanishing point, and estimating the vanishing point with these intersection points will seriously affect the accuracy of the vanishing point estimation

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  • A Tracking Method of Vanishing Point Based on Kalman Filter
  • A Tracking Method of Vanishing Point Based on Kalman Filter
  • A Tracking Method of Vanishing Point Based on Kalman Filter

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Embodiment Construction

[0052] The present invention provides a tracking method based on Kalman filter for trace vanishing points. The provided technology takes the image sequence collected by the vehicle-mounted camera as input, detects straight line segments in the image, and uses machine learning to exclude traces that do not contain or contain few traces. The line segment of the line block, so as to achieve the purpose of truly determining the vanishing point of the trace by the straight edge of the trace; the coordinates of the vanishing point of the trace are modeled as the state of the discrete dynamic system changing with time, and the vanishing point of the trace is tracked by the Kalman filter algorithm.

[0053] Such as figure 1 As shown, the Kalman filter-based trace vanishing point tracking method of the present invention may include the following steps 101-105:

[0054] Step 101: edge pixels are detected for the input image, and line segments are detected with the Hough transform algori...

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Abstract

The invention discloses a method for tracking the vanishing point of a trace line based on Kalman filtering, which belongs to the field of image processing. The present invention takes the image sequence collected by the vehicle-mounted camera as input, detects the straight line segment in the image, and excludes the line segment that does not contain or contains less line blocks by the method of machine learning, so as to achieve the real determination of the line extinction by the straight line edge of the line. point of purpose. Compared with the prior art, the present invention can reduce the impact of various interfering objects appearing in the field of vision on the estimation accuracy of the trace line vanishing point.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a tracking method for trace vanishing points based on Kalman filtering. Background technique [0002] Advanced Driver Assistance Systems (ADAS) use various sensors installed on the car to sense the surrounding environment during driving, collect data, identify, detect and track static and dynamic objects, and let the driver perceive possible The dangers that occur, thereby effectively increasing the comfort and safety of car driving. In the image collected by the camera equipped in the ADAS system, the parallel road lines on the road will converge at a point in the image, that is, the vanishing point. For applications such as lane line detection, lane departure warning, and front vehicle detection, the position of the vanishing point in the image is very important input information. [0003] Chinese patent 201610492617.9 discloses a vanishing point calibration method based on ho...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/277G06T7/13G06T7/168
CPCG06T2207/20061G06T2207/20081G06T2207/30256G06T7/13G06T7/168G06T7/277
Inventor 陈卫刚
Owner ZHEJIANG GONGSHANG UNIVERSITY
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