Vehicle-use image processing system, vehicle-use image processing method, vehicle-use image processing program, vehicle, and method of formulating vehicle-use image processing system
First Claim
1. A vehicle-use image processing system which performs image processing on the basis of a road surface image captured by an imaging device mounted on a vehicle, comprising:
- a reference area setting unit which sets a reference area corresponding to a road surface portion other than a lane mark in the road surface image captured by the imaging device;
a histogram preparing unit which prepares a histogram by measuring the frequency of luminance of each pixel of the road surface image in the reference area set by the reference area setting unit;
a road surface cluster extracting unit which extracts a cluster of portions, which are equal to or higher than a threshold value in width, height, or area, as a road surface cluster from the histogram prepared by the histogram preparing unit;
a lane mark candidate detecting unit which detects a lane mark candidate on the basis of the road surface image captured by the imaging device;
a luminance parameter calculating unit which calculates luminance parameters based on the luminance of the lane mark candidate detected by the lane mark candidate detecting unit; and
a lane mark detecting unit which detects a lane mark candidate whose luminance parameters calculated by the luminance parameter calculating unit fall within the luminance range of the road surface cluster extracted by the road surface cluster extracting unit as a false lane mark, while detecting a lane mark candidate whose luminance parameters calculated by the luminance parameter calculating unit fall off the luminance range of the road surface cluster extracted by the road surface cluster extracting unit as a true lane mark.
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Accused Products
Abstract
A system or the like capable of detecting lane marks more accurately by preventing false lane marks from being erroneously detected as true lane marks. A vehicle-use image processing system (100) allows a “road surface cluster” to be extracted from the “histogram” of luminance of each pixel in a “reference area” in a road surface image. Among “primary lane mark candidates,” those that overlap the “reference area” are detected as “secondary lane mark candidates.” Among the “secondary lane mark candidates,” those that have “luminance parameter” values falling within the luminance range of the “road surface cluster” are not detected as true lane marks. Thereby, lane marks are prevented from being erroneously detected (erroneous detection). This allows only lane marks to be detected more accurately.
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Citations
14 Claims
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1. A vehicle-use image processing system which performs image processing on the basis of a road surface image captured by an imaging device mounted on a vehicle, comprising:
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a reference area setting unit which sets a reference area corresponding to a road surface portion other than a lane mark in the road surface image captured by the imaging device; a histogram preparing unit which prepares a histogram by measuring the frequency of luminance of each pixel of the road surface image in the reference area set by the reference area setting unit; a road surface cluster extracting unit which extracts a cluster of portions, which are equal to or higher than a threshold value in width, height, or area, as a road surface cluster from the histogram prepared by the histogram preparing unit; a lane mark candidate detecting unit which detects a lane mark candidate on the basis of the road surface image captured by the imaging device; a luminance parameter calculating unit which calculates luminance parameters based on the luminance of the lane mark candidate detected by the lane mark candidate detecting unit; and a lane mark detecting unit which detects a lane mark candidate whose luminance parameters calculated by the luminance parameter calculating unit fall within the luminance range of the road surface cluster extracted by the road surface cluster extracting unit as a false lane mark, while detecting a lane mark candidate whose luminance parameters calculated by the luminance parameter calculating unit fall off the luminance range of the road surface cluster extracted by the road surface cluster extracting unit as a true lane mark. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 14)
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11. A vehicle-use image processing method of performing image processing on the basis of a road surface image captured by an imaging device mounted on a vehicle, comprising:
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a reference area setting step of setting a reference area corresponding to a road surface portion other than a lane mark in the road surface image captured by the imaging device; a histogram preparing step of preparing a histogram by measuring the frequency of luminance of each pixel of the road surface image in the reference area set in the reference area setting step; a road surface cluster extracting step of extracting a cluster of portions, which are equal to or higher than a threshold value in width, height, or area, as a road surface cluster from the histogram prepared in the histogram preparing step; a lane mark candidate detecting step of detecting a lane mark candidate on the basis of the road surface image captured by the imaging device; a luminance parameter calculating step of calculating luminance parameters based on the luminance of the lane mark candidate detected in the lane mark candidate detecting step; and a lane mark detecting step of detecting a lane mark candidate whose luminance parameters calculated in the luminance parameter calculating step fall within the luminance range of the road surface cluster extracted in the road surface cluster extracting step as a false lane mark, while detecting a lane mark candidate whose luminance parameters calculated in the luminance parameter calculating step fall off the luminance range of the road surface cluster extracted in the road surface cluster extracting step as a true lane mark.
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12. A vehicle-use image processing program stored on a non-transitory computer readable medium for giving functions of performing image processing on the basis of a road surface image captured by an imaging device mounted on a vehicle, wherein the program gives the computer:
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a reference area setting function of setting a reference area corresponding to a road surface portion other than a lane mark in the road surface image captured by the imaging device; a histogram preparing function of preparing a histogram by measuring the frequency of luminance of each pixel of the road surface image in the reference area set by the reference area setting function; a road surface cluster extracting function of extracting a cluster of portions, which are equal to or higher than a threshold value in width, height, or area, as a road surface cluster from the histogram prepared by the histogram preparing function; a lane mark candidate detecting function of detecting a lane mark candidate on the basis of the road surface image captured by the imaging device; a luminance parameter calculating function of calculating luminance parameters based on the luminance of the lane mark candidate detected by the lane mark candidate detecting function; and a lane mark detecting function of detecting a lane mark candidate whose luminance parameters calculated by the luminance parameter calculating function fall within the luminance range of the road surface cluster extracted by the road surface cluster extracting function as a false lane mark, while detecting a lane mark candidate whose luminance parameters calculated by the luminance parameter calculating function fall off the luminance range of the road surface cluster extracted by the road surface cluster extracting function as a true lane mark. - View Dependent Claims (13)
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Specification