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Traffic signal lamp identification method and device

A technology of traffic signal lights and recognition methods, applied in the field of traffic signal light recognition methods and devices, capable of solving problems such as decreased accuracy, blurred outlines of traffic signal lights, and reduced accuracy of traffic signal lights, achieving clear outlines, shortened time-consuming, and location extraction accurate effect

Active Publication Date: 2019-05-21
NEUSOFT REACH AUTOMOBILE TECH (SHENYANG) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, the identification of traffic lights mainly depends on the deep learning method. The road information in front of the vehicle is obtained through the camera installed on the vehicle, and then the color image captured by the camera is input into the neural network model for deep learning to obtain the position of the traffic lights, and then Obtain the state of the traffic signal lights, but because the outline of the traffic signal lights in the color image captured by the camera is often blurred, this reduces the accuracy of the traffic signal light morphological feature extraction during the deep learning process, thus reducing the accuracy of the traffic signal lights. The accuracy of positioning, which leads to the inability to accurately identify the status of the traffic lights

Method used

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  • Traffic signal lamp identification method and device
  • Traffic signal lamp identification method and device

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Experimental program
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Embodiment 1

[0040] Embodiment 1 of the present application provides a method for identifying a traffic signal, which will be described in detail below with reference to the accompanying drawings.

[0041] see figure 1 , which is a flowchart of a method for identifying a traffic signal provided in Embodiment 1 of the present application.

[0042] The method described in the embodiments of the present application includes the following steps:

[0043] S101: Acquire a color photographed image containing traffic lights.

[0044] The traffic signal light may be a lane signal light, a direction indicating signal light, or a signal light at a road and railway level crossing, which is not specifically limited in this application, and the number of the traffic signal lights is also not specifically limited in this application.

[0045] The captured image containing the traffic lights can be acquired in real time through the camera equipment installed on the vehicle, and the color captured image ...

Embodiment 2

[0067] Based on the method described in Embodiment 1, Embodiment 2 of the present application also provides another identification method for traffic lights, which will be described in detail below with reference to the accompanying drawings.

[0068] see figure 2 , which is a flow chart of another traffic signal recognition method provided in Embodiment 2 of the present application.

[0069] The method described in the embodiment of the present application includes the following steps:

[0070] S101: Acquire a color photographed image containing traffic lights.

[0071] S102: Convert the color captured image into a grayscale image.

[0072] S103a: Input the grayscale image into a preset deep learning model, identify the outline of the traffic signal light in the grayscale image through the deep learning model, and obtain the contour of the traffic signal light in the grayscale image location information.

[0073] The location information is a location frame of the traffi...

Embodiment 3

[0084] Based on the methods provided in the above embodiments, Embodiment 3 of the present application also provides a traffic signal recognition device, which will be described in detail below with reference to the accompanying drawings.

[0085] see image 3 , which is a structural diagram of an identification device for a traffic signal light provided in Embodiment 3 of the present application.

[0086] The device described in this embodiment of the present application includes: a first acquisition unit 301 , a conversion unit 302 , a second acquisition unit 303 and a third acquisition unit 304 .

[0087] The first acquisition unit 301 is configured to acquire a color photographed image containing traffic lights.

[0088] The color shot image is a color image, and the color shot image adopts the RGB color mode, and is obtained by changing the three color channels of red (R), green (G), and blue (B) and superimposing them with each other Assortment of colors.

[0089] The...

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Abstract

The invention provides a traffic signal lamp identification method. The method comprises the steps of obtaining a color shot image containing a traffic signal lamp; converting the color shot image into a grayscale image; obtaining the position information of the traffic signal lamp in the grayscale image, and obtaining the position information of the traffic signal lamp in the color shot image according to the position information of the traffic signal lamp in the grayscale image; and determining the current indication state information of the traffic signal lamp according to the position of the traffic signal lamp in the color shot image. By using the method provided by the invention, accurate positioning of the traffic signal lamp can be realized so as to accurately identify the state ofthe traffic signal lamp. The invention also provides a traffic signal lamp identification device.

Description

technical field [0001] The present application relates to the technical field of automatic driving, and in particular, to a method and device for identifying a traffic signal. Background technique [0002] The identification of traffic lights refers to the identification of the status of traffic lights on the basis of accurately locating the position of traffic lights. For example, red light, green light, yellow light, etc.) to determine the indication status of the traffic signal (for example, allow passage, prohibit passage, etc.). The identification of traffic lights can be used to judge the traffic status at traffic intersections, which is of great significance in automatic driving, navigation prompts, etc. [0003] At present, the recognition of traffic lights mainly relies on the deep learning method. The road information in front of the vehicle is obtained through the camera installed on the vehicle, and then the color image captured by the camera is input into the n...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N20/00G08G1/0962G08G1/0967
Inventor 张时嘉
Owner NEUSOFT REACH AUTOMOBILE TECH (SHENYANG) CO LTD
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