Road lane detection method based on binarization CGAN

A lane detection and binarization technology, applied in the field of image recognition, can solve the problem that the target recognition network is difficult to run embedded terminals, and achieve the effect of promoting application and delicate results

Pending Publication Date: 2020-05-12
合肥湛达智能科技有限公司
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  • Abstract
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Problems solved by technology

[0004] The present invention provides a highway lane detection method based on a binary CGAN network, which binarizes

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  • Road lane detection method based on binarization CGAN
  • Road lane detection method based on binarization CGAN
  • Road lane detection method based on binarization CGAN

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[0017] Example 1

[0018] A highway lane detection method based on a binary CGAN network, firstly constructs and trains a network model, and then detects highway lanes through the trained network model. figure 2 It is a schematic diagram of the network structure of the present invention, image 3 It is a schematic diagram of the lane detection output by the present invention.

[0019] The construction and training of the network model mainly includes the following steps:

[0020] 1. Collect a large number of road scene pictures, preprocess the pictures and label them to obtain a data set, and divide the data set into three parts: training set, test set and validation set.

[0021] The preprocessing mainly includes grayscale processing, smoothing processing, binarization processing, etc., and then use CAD to mark the lane markings. In order to distinguish it from the surrounding environment, a color with a large difference from the surrounding environment is selected for la...

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Abstract

The invention discloses a road lane detection method based on a binarization CGAN. The CGAN finally generates an extremely high resolution image. The details and textures of the image are the same asthose of a real picture, in the network training process, any manually defined loss function does not need to be relied on, and compared with a CNN and a SCNN, the CGAN has the advantages that the result is finer, smoother and more real, the network does not depend on more post-processing technologies and has great superiority; meanwhile, the CGAN is compressed, so that the CGAN can be possibly applied to the embedded terminal, and the application of a deep learning algorithm in movement is promoted.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a road lane detection method based on a binary CGAN network. Background technique [0002] At present, the research hotspot in the field of intelligent transportation is the safety driving assistance system, which mainly aims at how to reduce traffic accidents. By continuously developing advanced technologies to replace part of the driver's tasks, and constantly improving the car's assisted driving functions, a fully intelligent car will eventually be realized. In view of the increasing number of cars and the frequent occurrence of traffic accidents in recent years, many countries in the world have increased the research on the field of vehicle safety assisted driving. Vehicle departure warning is an important aspect of vehicle safety driving assistance system research, and it also plays an important role in intelligent system research. Lane detection and recognition ...

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/084G06V20/588G06N3/045
Inventor 吴善春张中
Owner 合肥湛达智能科技有限公司
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