Pavement water accumulation and ice accumulation detection method and apparatus thereof

Abstract

The present invention discloses a pavement water accumulation and ice accumulation detection method and an apparatus thereof. The method comprises: acquiring a first pavement image picture of a pavement positioned in an imaging range, wherein the first pavement image picture is captured by a first camera through a horizontal polarizer; acquiring a second pavement image picture of the pavement positioned in the imaging range, wherein the second pavement image picture is captured by a second camera through a vertical polarizer, wherein the imaging plane of an image sensor (CCD) of the second camera and the imaging plane of an CCD of the first camera are coplanar, and a distance between the second camera and the first camera does not exceed a predetermined value; and determining whether difference between brightness of the first pavement image picture and brightness of the second pavement image picture is larger than a predetermined brightness range, wherein the case that water accumulation or ice accumulation exists on the pavement positioned in the imaging range is determined if the difference between the brightness is larger than the predetermined brightness range. The apparatus can be promoted in the existing pavement detection camera, and has advantages of simple modification, low modification cost, and no influence on the original system.

Description

technical field [0001] The invention relates to the field of optical communications, in particular to a method and device for detecting water and ice accumulation on road areas. Background technique [0002] Traditional road condition monitors mainly use the principle of different absorption rates of infrared rays or microwaves on dry roads and ice and snow roads to detect road conditions. This detection method has the following disadvantages: limited sampling space, expensive, and cannot be used in a large area along the road. The layout and it is difficult to reflect the real situation of the entire road section. At present, Hiroshi FUKUI, Junichi TAKAGI et al. propose a method using image processing (see: Hiroshi Fukui, Junichi Takagi, Yoshiro Murata and Masashi Takeuchi.An Image Processing Method To Detect RoadSurface Condition Using Optical Spatial Frequency[J].IEEEConference on Intelligent Transportation System , 1997: 1005-1009.) to detect road conditions. This detec...

AI Technical Summary

Problems solved by technology

[0002] Traditional road condition monitors mainly use the principle of different absorption rates of infrared rays or microwaves on dry roads and ice and snow roads to detect road conditions. This detection method has the following disadvantages: limited sampling space, expensive, and cannot be used in a large area along the road. Layout and it is difficult to reflect the real situation of the entire road section

At present, Hiroshi FUKUI, Junichi TAKAGI et al. propose a method using image processing (see: Hiroshi Fukui, Junichi Takagi, Yoshiro Murata and Masashi Takeuchi.An Image Processing Method To Detect RoadSurface Condition Using Optical Spatial Frequency[J].IEEEConference on Intelligent Transportation System , 1997: 1005-1009.) to detect road conditions. This detection method uses the maximum full width and spatial frequency distribution of monitoring images to distinguish different road conditions. However, this method requires artificial light as an auxiliary and can only be used at night , and the position of the light source and the CCD camera is fixed, resulting in a small detection range, making it difficult to popularize and use

[0003] Currently, Yuukou Horita and Keiji Shibata et al. have also proposed an optical system to image vertically polarized images and horizontally polarized images at different positions of the camera (see: Yuukou Horita, Keiji Shibata, Kei Maeda, Yuji Hayashi. Omni-directional Polarization Image Sensor Based on an Omni-directional Camera and a Polarization Filter[C].Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance, 2009: 280-285.), however, this device requires special optical equipment (for example, The optical system has very strict requirements on the beam splitter), the imaging range and effect are not satisfactory, and it is difficult to apply in the existing monitoring scene; if the light is divided into two equal parts using a transflective sheet, complex optical system and double the number of cameras, it is also difficult to popularize it on a large scale

[0004] It can be seen that the road area water and ice detection method in the prior art has the problems of small detection range, high cost caused by complex detection devices, or complex detection methods, and a perfect technical solution has not yet been proposed for the above defects.

Images