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Road vanishing point detection method based on video images

A technology of video images and detection methods, applied in image analysis, image data processing, instruments, etc., can solve problems such as high error rate, complex voting algorithm, time consumption, etc.

Active Publication Date: 2014-09-17
HARBIN INST OF TECH
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to propose a road vanishing point detection method based on video images to solve the problem that the existing detection method has a high error rate, the traditional voting algorithm is more complicated, and most of the time is consumed in the voting algorithm. And there is a problem of large amount of calculation when using the multi-scale and multi-directional characteristics of Gabor wavelet for texture feature extraction

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  • Road vanishing point detection method based on video images
  • Road vanishing point detection method based on video images
  • Road vanishing point detection method based on video images

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specific Embodiment approach 1

[0038] Specific embodiment one: a kind of road vanishing point detection method based on video image described in this embodiment, comprises the following steps:

[0039] Step 1. Input a frame of image data I(x,y), convert it into a grayscale image and perform fast Fourier transform F{I(x,y)}, where x and y are the X axes of image pixels and Y-axis coordinates;

[0040] Step 2, the calculation of the texture response range based on the Gabor filter;

[0041] Step 3: Calculate the main direction of the image texture, the specific process is:

[0042] Step 31. Response to texture Sort in descending order to get E 1 ,E 2 ,E3 ,E 4 , and the corresponding Gabor filter angles are φ 1 , φ 2 , φ 3 and φ 4 ; where the Gabor filter used has a scale of s and a direction of φ i ;

[0043] Step three and two, define the confidence level of each pixel p(x,y): conf(p)=(E 1 -E 4 ) / E 1 , if the confidence conf(p) is greater than the predefined constant δ c And the maximum textu...

specific Embodiment approach 2

[0061] Specific embodiment two: the difference between this embodiment and specific embodiment one is: the calculation process described in step two is as follows:

[0062] Step 21, construct Gabor filter rectangular templates in four directions of 0°, 45°, 90°, and 135°, and perform fast discrete Fourier transform on the rectangular templates to obtain Scale is s, direction is φ i The time-domain form of the Gabor filter is as follows:

[0063] g s , φ i ( x , y ) = ω 2 π c e - ω 2 ( 4 a ...

specific Embodiment approach 3

[0069] Specific embodiment three: the difference between this embodiment and specific embodiment one or two is: the process of calculating the number of votes of particles described in step four is:

[0070] Step 41. Calculate the Euclidean distance d between the pixel p(x,y) and the particle v(i,j) and normalize it. On this basis, construct a distance function The process is as follows:

[0071] d = ( x - i ) 2 + ( y - j ) 2 - - - ( 7 )

[0072]

[0073] D ( p ) = L ...

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Abstract

The invention relates to a road vanishing point detection method, in particular to a road vanishing point detection method based on video images, and belongs to the field of road detection. The problems that an existing detection method is high in error rate, a traditional voting algorithm is complex, most of time is consumed by the voting algorithm, and the calculation quantity is large when the multi-scale and multi-direction characteristics of Gabor wavelets are used for extracting textural features are solved. The road vanishing point detection method is characterized by including the steps that a frame of image data are input and converted into a gray level image, and fast Fourier transform is carried out; the textural response range is calculated based on a Gabor filter; the main direction of image textures is calculated; the number of votes of particles is calculated; the range of particle distribution is adjusted; a dynamic observation model for vanishing points is set up; particle filtering is performed, and the vanishing points are output. The road vanishing point detection method can be applied to computer vision systems including an autonomous navigation system of an intelligent walking robot or a pilotless automobile and the like.

Description

technical field [0001] The invention relates to a method for detecting a road vanishing point, in particular to a method for detecting a road vanishing point based on a video image, and belongs to the field of road detection. Background technique [0002] Roads can be divided into structured roads and unstructured roads. Structured roads have relatively clear road markings and outline edges, and the road color is quite different from the surrounding environment. In comparison, unstructured roads are often not paved with cement or asphalt, and lack obvious road marking lines and boundaries. At the same time, the color of the road is often not significantly different from the surrounding background, such as muddy roads, snow or deserts, etc., making unstructured The reliable detection of roads has become a difficult point. In recent years, researchers at home and abroad have proposed a variety of vanishing point detection algorithms. However, due to the interference of strong ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 王进祥石金进高坤杜奥博付方发王永生陈少娜
Owner HARBIN INST OF TECH
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