Lane recognition image processing apparatus
First Claim
1. A lane recognition image processing apparatus installed on a vehicle for recognizing a lane based on a sensed image of at least one lane marking on the surface of a road, said apparatus comprising:
- an image sensing part for sensing a forward view of said vehicle;
an image storage part for temporarily storing images obtained by said image sensing part;
a window setting part for setting a search area for said at least one lane marking with respect to the images stored in said image storage part by means of a window;
a candidate point extraction part for extracting candidate points for said at least one lane marking from said search area set by said window setting part; and
a lane recognition part for deriving a lane marking mathematical model equation by approximating sets of candidate points extracted by said candidate point extraction part by a mathematical model equation. wherein said candidate point extraction part comprises;
a kernel size setting part that sets a kernel size Δ
h in accordance with a forward distance from said vehicle;
a one-dimensional image filtering part that outputs, as a filtering result, the smaller one of the values that are obtained by two equations {g(h)−
g(h−
Δ
h)} and {g(h)−
g(h+Δ
h)} using the gray value g(h) of a pixel of interest and the gray values g(h−
Δ
h), g(h+Δ
h) of pixels forwardly and rearwardly apart said kernel size Δ
h from said pixel of interest in a scanning direction, respectively; and
a binarization part that binarizes said filtering result with a threshold.
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Abstract
A lane recognition image processing apparatus can improve lane marking recognition performance by preventing false detection by addition of a condition without changing the basic principle of an one-dimensional image filter. A search area is set for each lane marking with respect to images stored in a image storage part through a window. A candidate point extraction part extracts candidate points of each lane marking from the search area thus set. A lane marking mathematical model equation is derived by approximating sets of extracted candidate points by a mathematical model equation. The candidate point extraction part includes a kernel size setting part, a filtering part that outputs, as a filtering result, the smaller of differences between the gray value of a pixel of interest and those of pixels forwardly and rearwardly apart a kernel size from the pixel of interest in a scanning direction, respectively, and a binarization part that binarizes the filtering result.
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Citations
6 Claims
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1. A lane recognition image processing apparatus installed on a vehicle for recognizing a lane based on a sensed image of at least one lane marking on the surface of a road, said apparatus comprising:
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an image sensing part for sensing a forward view of said vehicle;
an image storage part for temporarily storing images obtained by said image sensing part;
a window setting part for setting a search area for said at least one lane marking with respect to the images stored in said image storage part by means of a window;
a candidate point extraction part for extracting candidate points for said at least one lane marking from said search area set by said window setting part; and
a lane recognition part for deriving a lane marking mathematical model equation by approximating sets of candidate points extracted by said candidate point extraction part by a mathematical model equation. wherein said candidate point extraction part comprises;
a kernel size setting part that sets a kernel size Δ
h in accordance with a forward distance from said vehicle;
a one-dimensional image filtering part that outputs, as a filtering result, the smaller one of the values that are obtained by two equations {g(h)−
g(h−
Δ
h)} and {g(h)−
g(h+Δ
h)} using the gray value g(h) of a pixel of interest and the gray values g(h−
Δ
h), g(h+Δ
h) of pixels forwardly and rearwardly apart said kernel size Δ
h from said pixel of interest in a scanning direction, respectively; and
a binarization part that binarizes said filtering result with a threshold. - View Dependent Claims (2, 3, 4, 5, 6)
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Specification