CN108230241B - Fisheye image correction method for equipment with angle side mounting - Google Patents
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Abstract
The invention discloses a fisheye image correction method for equipment with an angle side mounting structure, which comprises the following steps: extracting the effective range of the fisheyes; carrying out barrel distortion coarse correction on the image; carrying out angle correction on the image; cutting the effective range of the corrected image; carrying out three-time Bezier curve back projection transformation on the image; and performing effective range cutting on the result image. The method can maximize the ratio of the effective area of the obtained original fisheye image, also can correct the fisheye image obtained when the side belt is carried at a certain angle, and has a good correction result on the fisheye image.
Description
Technical Field
The invention relates to an image correction method, in particular to a fisheye image correction method for equipment with an angle side mounting structure.
Background
A fisheye lens is a lens having a focal length of 16mm or less and a viewing angle close to or equal to 180 °. It is an extreme wide-angle lens. The fish-eye lens is one special lens in super wide angle lens, and its visual angle is required to reach or exceed the range visible to human eye. Due to the ultra-large wide angle of the fish-eye lens image, the image shot by the lens can have a very strong perspective effect, but the minded appeal has to be at the cost of very strong image distortion. The result of this distortion is that the scene is almost undistorted only in the center of the lens, and there is severe scene distortion elsewhere, the rule of this distortion being that the more distant the scene is from the center of the lens, the more severe the scene is deformed. In order to recover a real scene based on such a severely distorted image, geometric correction of the distorted image is required.
The correction method related in the prior art has the problems that the farther an image pixel point is from a central point, the more unsatisfactory the correction effect is, the too large cutting effective area after correction, algorithm design mostly aiming at a full-circle fisheye image and the like. Chinese patent publication No. CN104778656 discloses a fisheye image correction method of spherical perspective projection, which needs to calculate the mapping from the obtained fisheye image to the spherical surface, and this mapping process is not only large in calculation amount, but also mainly aims at the fisheye image of a full circle. Chinese patent publication No. CN103996172 discloses a fisheye image correction method based on multi-step correction, which not only requires a process of calibrating a camera lens, but also the farther the distance between the corrected image and the central point is, the more an elongated radial shape appears, the larger the area of the whole image to be cut, which is contrary to the purpose of using a fisheye lens to ensure a large field of view.
Disclosure of Invention
In order to make up for the defects of the prior art, the invention provides the fisheye image correction method with the angle side mounting, which utilizes the sensor to the maximum extent in the drum-shaped fisheye image, so that the effective monitoring area ratio of the obtained fisheye image is larger.
The invention is realized by the following technical scheme:
a fisheye image correction method for equipment with angle side mounting is characterized in that:
the method comprises the following steps:
s1, extracting the effective range of fish eyes:
collecting drum-shaped fisheye images, and extracting effective ranges of the collected original images by adopting a line-by-line scanning algorithm;
s2, carrying out barrel distortion coarse correction on the image:
s2.1, finding distortion factors of the optimal horizontal and vertical coordinates to be set as k1 and k 2;
s2.2, knowing that the barrel distortion mathematical model is ru=rd(1+krd 2) Wherein r isuDistance r from a pixel point in an undistorted image to the center of the imagedIs the distance from the pixel point to the center of the image after distortion, k is the distortion factor, since ru，rdAnd distortion abscissa xu，yuAnd xd，ydIn relation to this, the distortion formula can be obtained by substituting the distortion factor of the abscissa and ordinate in step S2.1 into the distortion mathematical model formula: x is the number ofu=xd(1+k1xd 2+k2yd 2)；
S2.3, since the barrel distortion correction has the abscissa symmetrical according to 1/2W and the ordinate symmetrical according to 1/2H, when traversing the image, the abscissa and the ordinate of the pixel point on the distorted image are (x) with 1/2W and 1/2H as boundary linesd，yd) The corrected undistorted image is (x)u，yu) L1 is the ordinate position of the current pixel, and L2 is the abscissa position of the current pixel, the following set of equations can be obtained:
yd = L1-H/2
xd = L2-W/2
xu = xd (1+ k1xd 2+k2yd 2) + W/2
yu = yd+ H/2
solving the fisheye image after barrel distortion correction according to the equation;
s3, angle correction is carried out on the image:
angle correction is performed on the image subjected to the coarse correction, and the image subjected to the coarse correction in the transverse direction and the longitudinal direction in S2 is used for angle correction;
s4, carrying out effective range cutting on the corrected image:
after the angle of the image is corrected, points which do not exist on the original image can be supplemented by black pixel points, so that a black area can be introduced into the local part of the image, and the corrected image is cut and extracted in an effective range by utilizing a line-by-line scanning algorithm;
s5, carrying out inverse projection transformation of the cubic Bezier curve on the image:
the Bezier curve cubic function formula is as follows:
B(t) = P0(1-t)3 + 3P1t(1-t)2 + 3P2t2(1-t) + P3t3
wherein, P0，P1，P2，P3For four points on the curve, reflected on the image, P0A point on the left border of the image, P3A point on the right border of the image, P1，P2The points are fixed as points on the whole image 1/3 and 2/3 respectively, t is an auxiliary parameter, and the value range is [0, 1 ]]B (t) is the corrected image coordinate, and assuming that the displacement on the y axis is k, the image width is W, the height is H, and the image curvature ratio is rate, four groups of point pairs respectively with P can be obtained0(0，k)，P1(W/3，H*rate + k)，P3(2W/3，H*rate + k)，P4(W, k), two sets of equations relating horizontal and vertical coordinates before and after correction can be obtained, and if x 'and y' are corrected image coordinates, then:
x’= P0x(1-t)3 + 3P1xt(1-t)2 + 3P2xt2(1-t) + P3xt3
y’= P0y(1-t)3 + 3P1yt(1-t)2 + 3P2yt2(1-t) + P3yt3
if the current abscissa is i, t = i/W, and a back projection formula of a cubic Bezier curve can be deduced under the condition that most parameters are fixed, so that each corrected fisheye image can find a corresponding point on the original image;
s6, performing effective range cutting on the result image:
and cutting and extracting the effective range of the corrected image by using a line-by-line scanning algorithm to finally obtain a fisheye image correction image obtained when the side surface is provided with an angle.
The invention discloses a fisheye image correction method for equipment with an angle side mounting, which comprises the following steps of extracting an effective range of an acquired original image by adopting a line-by-line scanning algorithm in step S1, wherein the method comprises the following specific steps:
s1.1, calculating the brightness of each pixel point of each line on the image, and determining the maximum brightness I of the pixel points of the linemaxAnd a minimum brightness IminThen the difference I of the brightness of the maximum pixel point of the rowsubComprises the following steps:
Isub=Imax-Imin
setting the boundary threshold value as T, scanning from left to right column by column, when IsubIf the scanning speed is more than T, the left edge of the drum-shaped fisheye image effective area is considered to be scanned;
s1.2, scanning pixel points of the fisheye image from right to left row by row according to the method of the step S1.1, and scanning a certain row of image pixel points Isub >When T is reached, the right edge of the effective area of the fisheye image is considered to be scanned;
and S1.3, intercepting the image by taking the left and right boundaries scanned in the step S1.1 and the step S1.2 as the boundaries of the effective area of the fisheye image.
Further, the value range of the boundary threshold T is 30-70, and preferably T = 50.
The invention discloses a fisheye image correction method for equipment with an angle side mounting, which is characterized in that the specific method for correcting the angle of an image in step S3 is as follows:
s3.1, assuming that the image before correction is rectangular, the width and height of the rectangle are respectively W1 and H1, the image after angle correction is trapezoidal, the upper bottom and the lower bottom are respectively W1 and W2, and the height is still H1, determining the width of W2 to obtain the positions of four vertexes of the image after angle correction, presetting an inclined angle alpha, and randomly changing the size of the angle according to the change of installation and angle, wherein the relation between the two images can be obtained:
W2=2×H1×tanα + W1
s3.2, the four vertex coordinates after angle correction are ((W2-W1)/2, 0), (W2+ (W2-W1)/2, 0), (0, H1), (W2, H1) respectively according to the width of the bottom W2 calculated by the formula;
s3.3, using the four vertex coordinate positions of the original image and the four vertex coordinate positions after the angle correction obtained in step S3.2, a homography matrix between the two images can be obtained, and since the homography matrix is a 3 × 3 matrix, it can be written as:
s3.4, let H22=1 to perform normalization, so that a homography matrix includes 8 unknowns and requires 8 equations to solve, and since two equations are provided for one point pair, H can be solved for four point pairs, and then the H mapping relationship between two graphs can be expressed as:
and S3.5, calculating the positions of all points of the image after angle correction point by using the homography matrix H obtained in the step S3.3.
Preferably, after the image is subjected to the inverse projection transformation of the cubic bezier curve in step S5, the corrected image is subjected to smooth interpolation by using a bilinear interpolation method to avoid the hole phenomenon.
Preferably, the effective range cutting extraction method for the image in steps S4 and S6 is the same as step S1.
The invention has the beneficial effects that: the method can maximize the ratio of the effective area of the obtained original fisheye image, also can correct the fisheye image obtained when the side is provided with a certain angle to a certain degree, so that the fisheye image does not have an obvious overlooking visual angle, can find the mapping point corresponding to the image without calibrating the lens of the camera, and has a good correction result on the fisheye image.
Drawings
FIG. 1 is a schematic flow chart of the calibration method of the present invention;
FIG. 2 is a schematic diagram of an acquired original fisheye image;
FIG. 3 is a schematic diagram of coordinates after and before image distortion correction;
FIG. 4 is a schematic illustration of an angle before and after correction;
fig. 5 is a schematic diagram of a cubic bezier curve.
Detailed Description
The present invention will be described in further detail with reference to the drawings and detailed description, so as to enable those skilled in the art to more fully, accurately and deeply understand the concept and technical solution of the present invention, and the scope of the present invention includes but is not limited to the following examples, and any modifications made to the details and form of the technical solution of the present invention can be made within the scope of the present invention without departing from the spirit and scope of the present application.
The drawing is an embodiment of the invention. The fisheye image correction method with the angle side mounting comprises the following steps:
s1, extracting the effective range of the fisheyes:
the drum-shaped fisheye image is collected, because the collected drum-shaped fisheye image has an invalid region as shown in the attached figure 2, the original image needs to be extracted in a limited range, a line-by-line scanning algorithm is adopted, and the specific method is as follows:
s1.1, calculating the brightness of each pixel point of each line on the image, and determining the maximum brightness I of the pixel points of the linemaxAnd a minimum brightness IminThen the difference I of the brightness of the maximum pixel point of the rowsubComprises the following steps:
Isub=Imax-Iminformula (1)
Setting the boundary threshold value as T =50 (T ranges from 30 to 70), scanning from left to right column by column, when I issubIf the scanning speed is more than T, the left edge of the drum-shaped fisheye image effective area is considered to be scanned;
s1.2, scanning pixel points of the fisheye image from right to left row by row according to the method of the step S1.1, and scanning a certain row of image pixel points Isub >When T is reached, the right edge of the effective area of the fisheye image is considered to be scanned;
and S1.3, intercepting the image by taking the left and right boundaries scanned in the step S1.1 and the step S1.2 as the boundaries of the effective area of the fisheye image.
S2, barrel distortion coarse correction is performed on the image:
the fisheye image with the effective area extracted is roughly corrected, and the obtained image is a drum-shaped fisheye image, and after the fisheye effective area is extracted, the whole image is similar to a barrel-shaped distorted image, so that the method for correcting barrel-shaped distortion can be used for roughly correcting the original fisheye image integrally, and the specific method comprises the following steps of:
s2.1, finding the distortion factor of the optimal abscissa and ordinate as k1, k2, in this embodiment, the factors such as the size of the integrated image, the distortion degree of the image, and the lens selection are preset to k1= -0.00000005, and k2= -0.0000007;
s2.2, as shown in fig. 3, the mathematical model of the known barrel distortion is:
ru=rd(1+krd 2) Formula (2)
Wherein r isuDistance r from a pixel point in an undistorted image to the center of the imagedIs the distance from the pixel point to the center of the image after distortion, k is the distortion factor (the distortion factor is related to the specific lens), since ru，rdAnd distortion abscissa xu，yuAnd xd，ydRegarding, substituting the distortion factor of the abscissa and ordinate in step S2.1 into equation (2), a deformation equation can be obtained:
xu=xd(1+k1xd 2+k2yd 2) Formula (3)
S2.3, since the barrel distortion correction has the abscissa symmetrical according to 1/2W and the ordinate symmetrical according to 1/2H, when traversing the image, the abscissa and the ordinate of the pixel point on the distorted image are (x) with 1/2W and 1/2H as boundary linesd，yd) The corrected undistorted image is (x)u，yu) L1 is the ordinate position of the current pixel, L2 is the abscissa position of the current pixel, and by combining equation (3), the following set of equations can be obtained:
yd= L1-H/2
xd= L2-W/2
xu= xd(1+ k1xd 2+k2yd 2) + W/2 formula (4)
yu= yd+ H/2
The fisheye image after barrel distortion correction can be obtained by the equation.
S3, angle correction of the image:
the angle correction is performed on the image subjected to the coarse correction, and the angle correction is performed by using the image subjected to the coarse correction in the horizontal and vertical directions in S2, specifically, the method includes:
s3.1, as shown in fig. 4, assuming that the width and height of the image before correction are W1 and H1, respectively, the upper bottom and lower bottom after angle correction are W1 and W2, respectively, and the height is still H1, determining the width of W2 can obtain the positions of the four vertices of the image after angle correction, the inclination angle is preset to 30 °, but the size of the angle can be changed arbitrarily according to the installation and the change of the angle, and the relationship between the two figures can be obtained:
w2=2 XH 1 ×/3+ W1 formula (5)
S3.2, the width of the bottom W2 obtained by the formula (5) can obtain four vertex coordinates after angle correction, namely ((W2-W1)/2, 0), (W2+ (W2-W1)/2, 0), (0, H1), (W2, H1);
s3.3, using the four vertex coordinate positions of the original image and the four vertex coordinate positions after the angle correction obtained in step S3.2, a homography matrix between the two images can be obtained, and since the homography matrix is a 3 × 3 matrix, it can be written as:
s3.4, it follows that a homography matrix contains 8 unknowns (typically normalized with H22= 1), 8 equations are needed to solve, and since one pair of points provides two equations, four pairs of points can solve for H. The H mapping relationship between the two graphs can be expressed as:
and S3.5, calculating the positions of all points of the image after angle correction point by using the homography matrix H obtained in the step S3.3.
S4, performing effective range cutting on the corrected image:
since the image is angularly corrected in step S3, and the points that do not exist on the original image after the angular correction are supplemented by black pixels, a black area is locally introduced into the image, and at this time, step S1 needs to be repeated, and the image after the angular correction is cut and extracted in the effective range by using the line-by-line scanning algorithm.
S5, carrying out inverse projection transformation on the image by using a cubic Bezier curve:
because the steps S2 and S4 only perform a distortion coarse correction and an angle correction on the fisheye image, the image still needs to be further corrected to ensure readability of image information, so a brand new fisheye image correction method is adopted, and the distorted fisheye image is secondarily corrected by using the back projection transformation of the cubic bezier curve;
as shown in fig. 5, the bezier curve can create and edit a smooth curve by controlling four points (a start point, an end point, and two mutually separated intermediate points) on the curve, where P is the drawing0Is the starting point of the curve, P3Is the end point of the curve, P1And P2Is a control point for controlling the trend of the curve, t is an auxiliary parameter, the value range of which is [0, 1 ]]The known cubic function formula is:
B(t) = at3 + bt2 + ct + d formula (7)
Bring in P0，P1，P2，P3Four points are available:
B(t) = P0(1-t)3 + 3P1t(1-t)2 + 3P2t2(1-t) + P3t3formula (8)
Reflected on the image, P0A point on the left border of the image, P3A point on the right border of the image, P1，P2The points are respectively fixed at the position 1/3 and the whole image 1/3 on the abscissa2/3, B (t) is the corrected image coordinate, let the displacement on the y-axis be k, the image width be W, the height be H, the image curvature ratio be rate (rate range is [0, 1 ]]) Then four groups of point pairs are obtained and are respectively P0(0，k)，P1(W/3，H*rate + k)，P3(2W/3，H*rate + k)，P4(W, k) substituted into equation (8) to obtain two sets of equations relating horizontal and vertical coordinates before and after correction, and assuming that x 'and y' are the corrected image coordinates, the following equations are obtained:
x’= P0x(1-t)3 + 3P1xt(1-t)2 + 3P2xt2(1-t) + P3xt3formula (9)
y’= P0y(1-t)3 + 3P1yt(1-t)2 + 3P2yt2(1-t) + P3yt3Formula (10)
And if the current abscissa is i, t = i/W, and a back projection formula of a cubic Bezier curve can be deduced under the condition that most parameters are fixed, so that each corrected fisheye image can find a corresponding point on the original image, the hole phenomenon is avoided, and finally, a bilinear interpolation method is used for carrying out smooth interpolation on the corrected image.
S6, performing effective range cutting on the result image
And repeating the step S1, and performing effective range cutting extraction on the corrected image by using a line-by-line scanning algorithm to finally obtain a fisheye image correction chart obtained when the side surface is provided with an angle.
Claims (6)
1. The fisheye image correction method for the equipment with the angle side mounting is characterized by comprising the following steps of: the method comprises the following steps:
s1, extracting the effective range of fish eyes:
collecting drum-shaped fisheye images, and extracting effective ranges of the collected original images by adopting a line-by-line scanning algorithm;
s2, carrying out barrel distortion coarse correction on the image:
s2.1, finding distortion factors of the optimal horizontal and vertical coordinates to be set as k1 and k 2;
s2.2, knowing that the barrel distortion mathematical model is ru=rd(1+krd 2) Wherein r isuDistance r from a pixel point in an undistorted image to the center of the imagedIs the distance from the pixel point to the center of the image after distortion, k is the distortion factor, since ru，rdAnd distortion abscissa xu，yuAnd xd，ydIn relation to this, the distortion formula can be obtained by substituting the distortion factor of the abscissa and ordinate in step S2.1 into the distortion mathematical model formula: x is the number ofu=xd(1+k1xd 2+k2yd 2)；
S2.3, since the barrel distortion correction has the abscissa symmetrical according to 1/2W and the ordinate symmetrical according to 1/2H, when traversing the image, the abscissa and the ordinate of the pixel point on the distorted image are (x) with 1/2W and 1/2H as boundary linesd，yd) The corrected undistorted image is (x)u，yu) L1 is the ordinate position of the current pixel, and L2 is the abscissa position of the current pixel, the following set of equations can be obtained:
yd = L1-H/2
xd = L2-W/2
xu = xd (1+ k1xd 2+k2yd 2) + W/2
yu = yd+ H/2
solving the fisheye image after barrel distortion correction according to the equation;
s3, angle correction is carried out on the image:
angle correction is performed on the image subjected to the coarse correction, and the image subjected to the coarse correction in the transverse direction and the longitudinal direction in S2 is used for angle correction;
s4, carrying out effective range cutting on the corrected image:
after the angle of the image is corrected, points which do not exist on the original image can be supplemented by black pixel points, so that a black area can be introduced into the local part of the image, and the corrected image is cut and extracted in an effective range by utilizing a line-by-line scanning algorithm;
s5, carrying out inverse projection transformation of the cubic Bezier curve on the image:
the Bezier curve cubic function formula is as follows:
B(t) = P0(1-t)3 + 3P1t(1-t)2 + 3P2t2(1-t) + P3t3
wherein, P0，P1，P2，P3For four points on the curve, reflected on the image, P0A point on the left border of the image, P3A point on the right border of the image, P1，P2The points are fixed as points on the whole image 1/3 and 2/3 respectively, t is an auxiliary parameter, and the value range is [0, 1 ]]B (t) is the corrected image coordinate, and assuming that the displacement on the y axis is k, the image width is W, the height is H, and the image curvature ratio is rate, four groups of point pairs respectively with P can be obtained0(0，k)，P1(W/3，H*rate + k)，P3(2W/3，H*rate + k)，P4(W, k), two sets of equations relating horizontal and vertical coordinates before and after correction can be obtained, and if x 'and y' are corrected image coordinates, then:
x’= P0x(1-t)3 + 3P1xt(1-t)2 + 3P2xt2(1-t) + P3xt3
y’= P0y(1-t)3 + 3P1yt(1-t)2 + 3P2yt2(1-t) + P3yt3
if the current abscissa is i, t = i/W, and a back projection formula of a cubic Bezier curve can be deduced under the condition that most parameters are fixed, so that each corrected fisheye image can find a corresponding point on the original image;
s6, performing effective range cutting on the result image:
and cutting and extracting the effective range of the corrected image by using a line-by-line scanning algorithm to finally obtain a fisheye image correction image obtained when the side surface is provided with an angle.
2. The method of claim 1 for correcting fisheye images mounted on an angled side of a device, wherein: in step S1, a column-by-column scanning algorithm is used to extract an effective range of the acquired original image, and the specific method is as follows:
s1.1, calculating the brightness of each pixel point of each line on the image, and determining the maximum brightness I of the pixel points of the linemaxAnd a minimum brightness IminThen the difference I of the brightness of the maximum pixel point of the rowsubComprises the following steps:
Isub=Imax-Imin
setting the boundary threshold value as T, scanning from left to right column by column, when IsubIf the scanning speed is more than T, the left edge of the drum-shaped fisheye image effective area is considered to be scanned;
s1.2, scanning pixel points of the fisheye image from right to left row by row according to the method of the step S1.1, and scanning a certain row of image pixel points Isub >When T is reached, the right edge of the effective area of the fisheye image is considered to be scanned;
and S1.3, intercepting the image by taking the left and right boundaries scanned in the step S1.1 and the step S1.2 as the boundaries of the effective area of the fisheye image.
3. The method of claim 2, wherein the fisheye image correction method is performed by an angle-side-mounted device, and comprises the following steps: the value range of the boundary threshold value T is 30-70.
4. The method of claim 1 for correcting fisheye images mounted on an angled side of a device, wherein: after the image is subjected to the inverse projection transformation of the cubic bezier curve in the step S5, to avoid the hole phenomenon, the corrected image is subjected to smooth interpolation by using a bilinear interpolation method.
5. The method for correcting fisheye images with an angle side device according to claim 2 or 3, characterized in that: the effective range cutting extraction method for the image in steps S4 and S6 is the same as step S1.
6. The method of claim 1 for correcting fisheye images mounted on an angled side of a device, wherein: step S3 is to perform angle correction on the image, specifically:
s3.1, assuming that the image before correction is rectangular, the width and height of the rectangle are respectively W1 and H1, the image after angle correction is trapezoidal, the upper bottom and the lower bottom are respectively W1 and W2, and the height is still H1, determining the width of W2 to obtain the positions of four vertexes of the image after angle correction, presetting an inclined angle alpha, and randomly changing the size of the angle according to the change of installation and angle, wherein the relation between the two images can be obtained:
W2=2×H1×tanα + W1
s3.2, the four vertex coordinates after angle correction are ((W2-W1)/2, 0), (W2+ (W2-W1)/2, 0), (0, H1), (W2, H1) respectively according to the width of the bottom W2 calculated by the formula;
s3.3, using the four vertex coordinate positions of the original image and the four vertex coordinate positions after the angle correction obtained in step S3.2, a homography matrix between the two images can be obtained, and since the homography matrix is a 3 × 3 matrix, it can be written as:
s3.4, let H22=1 to perform normalization, so that a homography matrix includes 8 unknowns and requires 8 equations to solve, and since two equations are provided for one point pair, H can be solved for four point pairs, and then the H mapping relationship between two graphs can be expressed as:
and S3.5, calculating the positions of all points of the image after angle correction point by using the homography matrix H obtained in the step S3.3.
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