I am trying to implement the Cubic Interpolation method using the next formula when a=-0.5 as usual.
My Linear Interpolation and Nearest Neighbor interpolation is working great but for some reason the Cubic interpolation fails with white pixels and turn them sometimes to turquoise color and sometimes messing around with another colors.
for example using rotation: (NOTE: please look carefully on the right image and you will notice the problems)
Another Example with much more black pixels. It almost seems to work perfectly but look on the dog's tongue. (strong white pixels turn to turquoise again)
you can see that my implementation of the Linear Interpolation is working great:
Since the actual rotation worked, I think I have a small mistake in the code that I did not notice, or maybe it's a numeric error or a double / float error.
It is important to note that I read the image normally and store the destination image as follows:
cv::Mat img = cv::imread("../dogfails.jpeg");
cv::Mat rotatedImageCubic(img.rows,img.cols,CV_8UC3);
Clarifications:
Inside my cubic interpolation function, srcPoint (newX and newY) is the "landing point" from the inverse transformation.
In my inverse transformations I am not using matrix multiplication with the pixels, right now I am just using the formulas for rotation. It might be important for the "numerical errors". For example:
rotatedX = x * cos(angle * toRadian) + y * sin(angle * toRadian);
rotatedY = x * (-sin(angle * toRadian)) + y * cos(angle * toRadian);
Here is my code for the Cubic Interpolation
double cubicEquationSolver(double d,double a) {
d = abs(d);
if( 0.0 <= d && d <= 1.0) {
double score = (a + 2.0) * pow(d, 3.0) - ((a + 3.0) * pow(d, 2.0)) + 1.0;
return score;
}
else if(1 < d && d <= 2) {
double score = a * pow(d, 3.0) - 5.0*a * pow(d, 2.0) + 8.0*a * d - 4.0*a;
return score;
}
else
return 0.0;
}
void Cubic_Interpolation_Helper(const cv::Mat& src, cv::Mat& dst, const cv::Point2d& srcPoint, cv::Point2i& dstPixel) {
double newX = srcPoint.x;
double newY = srcPoint.y;
double dx = abs(newX - round(newX));
double dy = abs(newY - round(newY));
double sumCubicBValue = 0;
double sumCubicGValue = 0;
double sumCubicRValue = 0;
double sumCubicGrayValue = 0;
double uX = 0;
double uY = 0;
if (floor(newX) - 1 < 0 || floor(newX) + 2 > src.cols - 1 || floor(newY) < 0 || floor(newY) > src.rows - 1) {
if (dst.channels() > 1)
dst.at<cv::Vec3b>(dstPixel) = cv::Vec3b(0, 0,0);
else
dst.at<uchar>(dstPixel) = 0;
}
else {
for (int cNeighbor = -1; cNeighbor <= 2; cNeighbor++) {
for (int rNeighbor = -1; rNeighbor <= 2; rNeighbor++) {
uX = cubicEquationSolver(rNeighbor + dx, -0.5);
uY = cubicEquationSolver(cNeighbor + dy, -0.5);
if (src.channels() > 1) {
sumCubicBValue = sumCubicBValue + (double) src.at<cv::Vec3b>(
cv::Point2i(round(newX) + rNeighbor, cNeighbor + round(newY)))[0] * uX * uY;
sumCubicGValue = sumCubicGValue + (double) src.at<cv::Vec3b>(
cv::Point2i(round(newX) + rNeighbor, cNeighbor + round(newY)))[1] * uX * uY;
sumCubicRValue = sumCubicRValue + (double) src.at<cv::Vec3b>(
cv::Point2i(round(newX) + rNeighbor, cNeighbor + round(newY)))[2] * uX * uY;
} else {
sumCubicGrayValue = sumCubicGrayValue + (double) src.at<uchar>(
cv::Point2i(round(newX) + rNeighbor, cNeighbor + round(newY))) * uX * uY;
}
}
}
if (dst.channels() > 1)
dst.at<cv::Vec3b>(dstPixel) = cv::Vec3b((int) round(sumCubicBValue), (int) round(sumCubicGValue),
(int) round(sumCubicRValue));
else
dst.at<uchar>(dstPixel) = sumCubicGrayValue;
}
I hope someone here will be able to help me, Thanks!
After advice from krlzlx I have posted it as a new question.
From here:
3D Line Segment and Plane Intersection
I have a problem with this algorithm, I have implemented it like so:
template <class T>
class AnyCollision {
public:
std::pair<bool, T> operator()(Point3d &ray, Point3d &rayOrigin, Point3d &normal, Point3d &coord) const {
// get d value
float d = (normal.x * coord.x) + (normal.y * coord.y) + (normal.z * coord.z);
if (((normal.x * ray.x) + (normal.y * ray.y) + (normal.z * ray.z)) == 0) {
return std::make_pair(false, T());
}
// Compute the X value for the directed line ray intersecting the plane
float a = (d - ((normal.x * rayOrigin.x) + (normal.y * rayOrigin.y) + (normal.z * rayOrigin.z)) / ((normal.x * ray.x) + (normal.y * ray.y) + (normal.z * ray.z)));
// output contact point
float rayMagnitude = (sqrt(pow(ray.x, 2) + pow(ray.y, 2) + pow(ray.z, 2)));
Point3d rayNormalised((ray.x / rayMagnitude), (ray.y / rayMagnitude), (ray.z / rayMagnitude));
Point3d contact((rayOrigin.x + (rayNormalised.x * a)), (rayOrigin.y + (rayNormalised.y * a)), (rayOrigin.z + (rayNormalised.z * a))); //Make sure the ray vector is normalized
return std::make_pair(true, contact);
};
Point3d is defined as:
class Point3d {
public:
double x;
double y;
double z;
/**
* constructor
*
* 0 all elements
*/
Point3d() {
x = 0.0;
y = 0.0;
z = 0.0;
}
I am forced to use this structure, because in the larger system my component runs in it is defined like this and it cannot be changed.
My code compiles fine, but testing I get incorrect values for the point. The ratio of x, y, z is correct but the magnitude is wrong.
For example if:
rayOrigin.x = 0;
rayOrigin.y = 0;
rayOrigin.z = 0;
ray.x = 3;
ray.y = -5;
ray.z = 12;
normal.x = -3;
normal.y = 12;
normal.z = 0;
coord.x = 7;
coord.y = -5;
coord.z = 10;
I expect the point to be:
(0.63, 1.26, 1.89)
However, it is:
(3.52, -5.87, 14.09)
A magnitude of 5.09 too big.
And I also tested:
rayOrigin.x = 0;
rayOrigin.y = 0;
rayOrigin.z = 0;
ray.x = 2;
ray.y = 3;
ray.z = 3;
normal.x = 4;
normal.y = 1;
normal.z = 0;
p0.x = 2;
p0.y = 1;
p0.z = 5;
I expect the point to be:
(1.64, 2.45, 2.45)
However, it is:
(3.83761, 5.75642, 5.75642)
A magnitude of 2.34 too big?
Pseudocode (does not require vector normalization):
Diff = PlaneBaseCoordinate - RayOrigin
d = Normal.dot.Diff
e = Normal.dot.RayVector
if (e)
IntersectionPoint = RayOrigin + RayVector * d / e
otherwise
ray belongs to the plane or is parallel
Quick check:
Ray (0,0,0) (2,2,2) //to catch possible scale issues
Plane (0,1,0) (0,3,0) //plane y=1
Diff = (0,1,0)
d = 3
e = 6
IntersectionPoint = (0,0,0) + (2,2,2) * 3 / 6 = (1, 1, 1)
I'm researching how to find the inertia for a 2D shape. The contour of this shape is meshed with several points, the x and y coordinate of each point is already known.
I know the expression of Ixx, Iyy and Ixy but the body has no mass. How do I proceed?
For whatever shape you have, you need to split it into triangles and handle each triangle separately. Then in the end combined the results using the following rules
Overall
% Combined total area of all triangles
total_area = SUM( area(i), i=1:n )
total_mass = SUM( mass(i), i=1:n )
% Combined centroid (center of mass) coordinates
combined_centroid_x = SUM( mass(i)*centroid_x(i), i=1:n)/total_mass
combined_centroid_y = SUM( mass(i)*centroid_y(i), i=1:n)/total_mass
% Each distance to triangle (squared)
centroid_distance_sq(i) = centroid_x(i)*centroid_x(i)+centroid_y(i)*centroid_y(i)
% Combined mass moment of inertia
combined_mmoi = SUM(mmoi(i)+mass(i)*centroid_distance_sq(i), i=1:n)
Now for each triangle.
Consider the three corner vertices with vector coordinates, points A, B and C
a=[ax,ay]
b=[bx,by]
c=[cx,cy]
and the following dot and cross product (scalar) combinations
a·a = ax*ax+ay*ay
b·b = bx*bx+by*by
c·c = cx*cx+cy*cy
a·b = ax*bx+ay*by
b·c = bx*cx+by*cy
c·a = cx*ax+cy*ay
a×b = ax*by-ay*bx
b×c = bx*cy-by*cx
c×a = cx*ay-cy*ax
The properties of the triangle are (with t(i) the thickness and rho the mass density)
area(i) = 1/2*ABS( a×b + b×c + c×a )
mass(i) = rho*t(i)*area(i)
centroid_x(i) = 1/3*(ax + bx + cx)
centroid_y(i) = 1/3*(ay + by + cy)
mmoi(i) = 1/6*mass(i)*( a·a + b·b + c·c + a·b + b·c + c·a )
By component the above are
area(i) = 1/2*ABS( ax*(by-cy)+ay*(cx-bx)+bx*cy-by*cx)
mmoi(i) = mass(i)/6*(ax^2+ax*(bx+cx)+bx^2+bx*cx+cx^2+ay^2+ay*(by+cy)+by^2+by*cy+cy^2)
Appendix
A little theory here. The area of each triangle is found using
Area = 1/2 * || (b-a) × (c-b) ||
where × is a vector cross product, and || .. || is vector norm (length function).
The triangle is parametrized by two variables t and s such that the double integral A = INT(INT(1,dx),dy) gives the total area
% position r(s,t) = [x,y]
[x,y] = [ax,ay] + t*[bx-ax, by-zy] + t*s*[cx-bx,cy-by]
% gradient directions along s and t
(dr/dt) = [bx-ax,by-ay] + s*[cx-bx,cy-by]
(dr/ds) = t*[cx-bx,cy-by]
% Integration area element
dA = || (dr/ds)×(dr/dt) || = (2*A*t)*ds*dt
%
% where A = 1/2*||(b-a)×(c-b)||
% Check that the integral returns the area
Area = INT( INT( 2*A*t,s=0..1), t=0..1) = 2*A*(1/2) = A
% Mass moment of inertia components
/ / / | y^2+z^2 -x*y -x*z |
I = 2*m*| | | t*| -x*y x^2+z^2 -y*z | dz ds dt
/ / / | -x*z -y*z x^2+y^2 |
% where [x,y] are defined from the parametrization
I want to slightly correct excellent John Alexiou answer:
Triangle mmoi algorithm expects corners to be defined relative to triangle center of mass (centroid). So subtract centroid from corners before calculating mmoi
Shape mmoi algorithm expects centroids of each single triangle to be defined relative to shape center of mass (combined centroid). So subtract combined centroid from each triangle centroid before calculating mmoi.
So result code would look like this:
public static float CalculateMMOI(Triangle[] triangles, float thickness, float density)
{
float[] mass = new float[triangles.Length];
float[] mmoi = new float[triangles.Length];
Vector2[] centroid = new Vector2[triangles.Length];
float combinedMass = 0;
float combinedMMOI = 0;
Vector2 combinedCentroid = new Vector2(0, 0);
for (var i = 0; i < triangles.Length; ++i)
{
mass[i] = triangles[i].CalculateMass(thickness, density);
mmoi[i] = triangles[i].CalculateMMOI(mass[i]);
centroid[i] = triangles[i].CalculateCentroid();
combinedMass += mass[i];
combinedCentroid += mass[i] * centroid[i];
}
combinedCentroid /= combinedMass;
for (var i = 0; i < triangles.Length; ++i) {
combinedMMOI += mmoi[i] + mass[i] * (centroid[i] - combinedCentroid).LengthSquared();
}
return combinedMMOI;
}
public struct Triangle
{
public Vector2 A, B, C;
public float CalculateMass(float thickness, float density)
{
var area = CalculateArea();
return area * thickness * density;
}
public float CalculateArea()
{
return 0.5f * Math.Abs(Vector2.Cross(A - B, A - C));
}
public float CalculateMMOI(float mass)
{
var centroid = CalculateCentroid()
var a = A - centroid;
var b = B - centroid;
var c = C - centroid;
var aa = Vector2.Dot(a, a);
var bb = Vector2.Dot(b, b);
var cc = Vector2.Dot(c, c);
var ab = Vector2.Dot(a, b);
var bc = Vector2.Dot(b, c);
var ca = Vector2.Dot(c, a);
return (aa + bb + cc + ab + bc + ca) * mass / 6f;
}
public Vector2 CalculateCentroid()
{
return (A + B + C) / 3f;
}
}
public struct Vector2
{
public float X, Y;
public float LengthSquared()
{
return X * X + Y * Y;
}
public static float Dot(Vector2 a, Vector2 b)
{
return a.X * b.X + a.Y * b.Y;
}
public static float Cross(Vector2 a, Vector2 b)
{
return a.X * b.Y - a.Y * b.X;
}
}
I have a uint8_t YUYV 422 (Interleaved) image array in memory and I want to be able to flip it both vertically and horizontally. I have successfully implemented a vertical flip but I'm having a problem with flipping both horizontally and vertically at the same time.
My code for the vertical flip, below, works perfectly.
int counter = 0;
int array_width = 2; // YUYV
for (int h = (m_Width * m_Height * array_width) - m_Width * array_width; h > 0; h -= m_Width * array_width)
{
for (int w = 0; w < m_Width * array_width; w++)
{
flipped[counter] = buffer[h + w];
counter++;
}
}
However, the following vertical and horizontal flip code appears to work but there is a loss of definition. To better understand what I am referring to, please see my sample images.
int x = 0;
for (int n = m_Width * m_Height * 2 - 1; n >= 0; n -= 4)
{
flipped[x] = buffer[n - 3]; // Y0
flipped[x + 1] = buffer[n - 2]; // U
flipped[x + 2] = buffer[n - 1]; // Y1
flipped[x + 3] = buffer[n]; // V
x += 4;
}
As you can see, I am moving the YUYV components and keeping them in the same order. I don't believe that I am dropping pixels so I don't understand why I am losing definition. To reiterate, I don't see this problem when flipping vertically (Using the first code snippet).
Here is the reference image, please note the stem of the lamp:
This is the flipped image, the stem of the lamp has lost definition:
You also need to swap Y0 and Y1 in your loop.
int x = 0;
for (int n = m_Width * m_Height * 2 - 1; n >= 3; n -= 4)
{
flipped[x] = buffer[n - 1]; // Y1->Y0
flipped[x + 1] = buffer[n - 2]; // U
flipped[x + 2] = buffer[n - 3]; // Y0->Y1
flipped[x + 3] = buffer[n]; // V
x += 4;
}
While I was at it, since you're accessing n - 3 I changed the loop condition to be absolutely sure it was safe.
m_Width * m_Height * 2 is not a multiple of 4 (the number of data blocks in YUYV format. Try changing '2' into '4', an also array_width.
I have an ellipse, defined by Center Point, radiusX and radiusY, and I have a Point. I want to find the point on the ellipse that is closest to the given point. In the illustration below, that would be S1.
Now I already have code, but there is a logical error somewhere in it, and I seem to be unable to find it. I broke the problem down to the following code example:
#include <vector>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <math.h>
using namespace std;
void dostuff();
int main()
{
dostuff();
return 0;
}
typedef std::vector<cv::Point> vectorOfCvPoints;
void dostuff()
{
const double ellipseCenterX = 250;
const double ellipseCenterY = 250;
const double ellipseRadiusX = 150;
const double ellipseRadiusY = 100;
vectorOfCvPoints datapoints;
for (int i = 0; i < 360; i+=5)
{
double angle = i / 180.0 * CV_PI;
double x = ellipseRadiusX * cos(angle);
double y = ellipseRadiusY * sin(angle);
x *= 1.4;
y *= 1.4;
x += ellipseCenterX;
y += ellipseCenterY;
datapoints.push_back(cv::Point(x,y));
}
cv::Mat drawing = cv::Mat::zeros( 500, 500, CV_8UC1 );
for (int i = 0; i < datapoints.size(); i++)
{
const cv::Point & curPoint = datapoints[i];
const double curPointX = curPoint.x;
const double curPointY = curPoint.y * -1; //transform from image coordinates to geometric coordinates
double angleToEllipseCenter = atan2(curPointY - ellipseCenterY * -1, curPointX - ellipseCenterX); //ellipseCenterY * -1 for transformation to geometric coords (from image coords)
double nearestEllipseX = ellipseCenterX + ellipseRadiusX * cos(angleToEllipseCenter);
double nearestEllipseY = ellipseCenterY * -1 + ellipseRadiusY * sin(angleToEllipseCenter); //ellipseCenterY * -1 for transformation to geometric coords (from image coords)
cv::Point center(ellipseCenterX, ellipseCenterY);
cv::Size axes(ellipseRadiusX, ellipseRadiusY);
cv::ellipse(drawing, center, axes, 0, 0, 360, cv::Scalar(255));
cv::line(drawing, curPoint, cv::Point(nearestEllipseX,nearestEllipseY*-1), cv::Scalar(180));
}
cv::namedWindow( "ellipse", CV_WINDOW_AUTOSIZE );
cv::imshow( "ellipse", drawing );
cv::waitKey(0);
}
It produces the following image:
You can see that it actually finds "near" points on the ellipse, but it are not the "nearest" points. What I intentionally want is this: (excuse my poor drawing)
would you extent the lines in the last image, they would cross the center of the ellipse, but this is not the case for the lines in the previous image.
I hope you get the picture. Can anyone tell me what I am doing wrong?
Consider a bounding circle around the given point (c, d), which passes through the nearest point on the ellipse. From the diagram it is clear that the closest point is such that a line drawn from it to the given point must be perpendicular to the shared tangent of the ellipse and circle. Any other points would be outside the circle and so must be further away from the given point.
So the point you are looking for is not the intersection between the line and the ellipse, but the point (x, y) in the diagram.
Gradient of tangent:
Gradient of line:
Condition for perpedicular lines - product of gradients = -1:
When rearranged and substituted into the equation of your ellipse...
...this will give two nasty quartic (4th-degree polynomial) equations in terms of either x or y. AFAIK there are no general analytical (exact algebraic) methods to solve them. You could try an iterative method - look up the Newton-Raphson iterative root-finding algorithm.
Take a look at this very good paper on the subject:
http://www.spaceroots.org/documents/distance/distance-to-ellipse.pdf
Sorry for the incomplete answer - I totally blame the laws of mathematics and nature...
EDIT: oops, i seem to have a and b the wrong way round in the diagram xD
There is a relatively simple numerical method with better convergence than Newtons Method. I have a blog post about why it works http://wet-robots.ghost.io/simple-method-for-distance-to-ellipse/
This implementation works without any trig functions:
def solve(semi_major, semi_minor, p):
px = abs(p[0])
py = abs(p[1])
tx = 0.707
ty = 0.707
a = semi_major
b = semi_minor
for x in range(0, 3):
x = a * tx
y = b * ty
ex = (a*a - b*b) * tx**3 / a
ey = (b*b - a*a) * ty**3 / b
rx = x - ex
ry = y - ey
qx = px - ex
qy = py - ey
r = math.hypot(ry, rx)
q = math.hypot(qy, qx)
tx = min(1, max(0, (qx * r / q + ex) / a))
ty = min(1, max(0, (qy * r / q + ey) / b))
t = math.hypot(ty, tx)
tx /= t
ty /= t
return (math.copysign(a * tx, p[0]), math.copysign(b * ty, p[1]))
Credit to Adrian Stephens for the Trig-Free Optimization.
Here is the code translated to C# implemented from this paper to solve for the ellipse:
http://www.geometrictools.com/Documentation/DistancePointEllipseEllipsoid.pdf
Note that this code is untested - if you find any errors let me know.
//Pseudocode for robustly computing the closest ellipse point and distance to a query point. It
//is required that e0 >= e1 > 0, y0 >= 0, and y1 >= 0.
//e0,e1 = ellipse dimension 0 and 1, where 0 is greater and both are positive.
//y0,y1 = initial point on ellipse axis (center of ellipse is 0,0)
//x0,x1 = intersection point
double GetRoot ( double r0 , double z0 , double z1 , double g )
{
double n0 = r0*z0;
double s0 = z1 - 1;
double s1 = ( g < 0 ? 0 : Math.Sqrt(n0*n0+z1*z1) - 1 ) ;
double s = 0;
for ( int i = 0; i < maxIter; ++i ){
s = ( s0 + s1 ) / 2 ;
if ( s == s0 || s == s1 ) {break; }
double ratio0 = n0 /( s + r0 );
double ratio1 = z1 /( s + 1 );
g = ratio0*ratio0 + ratio1*ratio1 - 1 ;
if (g > 0) {s0 = s;} else if (g < 0) {s1 = s ;} else {break ;}
}
return s;
}
double DistancePointEllipse( double e0 , double e1 , double y0 , double y1 , out double x0 , out double x1)
{
double distance;
if ( y1 > 0){
if ( y0 > 0){
double z0 = y0 / e0;
double z1 = y1 / e1;
double g = z0*z0+z1*z1 - 1;
if ( g != 0){
double r0 = (e0/e1)*(e0/e1);
double sbar = GetRoot(r0 , z0 , z1 , g);
x0 = r0 * y0 /( sbar + r0 );
x1 = y1 /( sbar + 1 );
distance = Math.Sqrt( (x0-y0)*(x0-y0) + (x1-y1)*(x1-y1) );
}else{
x0 = y0;
x1 = y1;
distance = 0;
}
}
else // y0 == 0
x0 = 0 ; x1 = e1 ; distance = Math.Abs( y1 - e1 );
}else{ // y1 == 0
double numer0 = e0*y0 , denom0 = e0*e0 - e1*e1;
if ( numer0 < denom0 ){
double xde0 = numer0/denom0;
x0 = e0*xde0 ; x1 = e1*Math.Sqrt(1 - xde0*xde0 );
distance = Math.Sqrt( (x0-y0)*(x0-y0) + x1*x1 );
}else{
x0 = e0;
x1 = 0;
distance = Math.Abs( y0 - e0 );
}
}
return distance;
}
The following python code implements the equations described at "Distance from a Point to an Ellipse" and uses newton's method to find the roots and from that the closest point on the ellipse to the point.
Unfortunately, as can be seen from the example, it seems to only be accurate outside the ellipse. Within the ellipse weird things happen.
from math import sin, cos, atan2, pi, fabs
def ellipe_tan_dot(rx, ry, px, py, theta):
'''Dot product of the equation of the line formed by the point
with another point on the ellipse's boundary and the tangent of the ellipse
at that point on the boundary.
'''
return ((rx ** 2 - ry ** 2) * cos(theta) * sin(theta) -
px * rx * sin(theta) + py * ry * cos(theta))
def ellipe_tan_dot_derivative(rx, ry, px, py, theta):
'''The derivative of ellipe_tan_dot.
'''
return ((rx ** 2 - ry ** 2) * (cos(theta) ** 2 - sin(theta) ** 2) -
px * rx * cos(theta) - py * ry * sin(theta))
def estimate_distance(x, y, rx, ry, x0=0, y0=0, angle=0, error=1e-5):
'''Given a point (x, y), and an ellipse with major - minor axis (rx, ry),
its center at (x0, y0), and with a counter clockwise rotation of
`angle` degrees, will return the distance between the ellipse and the
closest point on the ellipses boundary.
'''
x -= x0
y -= y0
if angle:
# rotate the points onto an ellipse whose rx, and ry lay on the x, y
# axis
angle = -pi / 180. * angle
x, y = x * cos(angle) - y * sin(angle), x * sin(angle) + y * cos(angle)
theta = atan2(rx * y, ry * x)
while fabs(ellipe_tan_dot(rx, ry, x, y, theta)) > error:
theta -= ellipe_tan_dot(
rx, ry, x, y, theta) / \
ellipe_tan_dot_derivative(rx, ry, x, y, theta)
px, py = rx * cos(theta), ry * sin(theta)
return ((x - px) ** 2 + (y - py) ** 2) ** .5
Here's an example:
rx, ry = 12, 35 # major, minor ellipse axis
x0 = y0 = 50 # center point of the ellipse
angle = 45 # ellipse's rotation counter clockwise
sx, sy = s = 100, 100 # size of the canvas background
dist = np.zeros(s)
for x in range(sx):
for y in range(sy):
dist[x, y] = estimate_distance(x, y, rx, ry, x0, y0, angle)
plt.imshow(dist.T, extent=(0, sx, 0, sy), origin="lower")
plt.colorbar()
ax = plt.gca()
ellipse = Ellipse(xy=(x0, y0), width=2 * rx, height=2 * ry, angle=angle,
edgecolor='r', fc='None', linestyle='dashed')
ax.add_patch(ellipse)
plt.show()
Which generates an ellipse and the distance from the boundary of the ellipse as a heat map. As can be seen, at the boundary the distance is zero (deep blue).
Given an ellipse E in parametric form and a point P
the square of the distance between P and E(t) is
The minimum must satisfy
Using the trigonometric identities
and substituting
yields the following quartic equation:
Here's an example C function that solves the quartic directly and computes sin(t) and cos(t) for the nearest point on the ellipse:
void nearest(double a, double b, double x, double y, double *ecos_ret, double *esin_ret) {
double ax = fabs(a*x);
double by = fabs(b*y);
double r = b*b - a*a;
double c, d;
int switched = 0;
if (ax <= by) {
if (by == 0) {
if (r >= 0) { *ecos_ret = 1; *esin_ret = 0; }
else { *ecos_ret = 0; *esin_ret = 1; }
return;
}
c = (ax - r) / by;
d = (ax + r) / by;
} else {
c = (by + r) / ax;
d = (by - r) / ax;
switched = 1;
}
double cc = c*c;
double D0 = 12*(c*d + 1); // *-4
double D1 = 54*(d*d - cc); // *4
double D = D1*D1 + D0*D0*D0; // *16
double St;
if (D < 0) {
double t = sqrt(-D0); // *2
double phi = acos(D1 / (t*t*t));
St = 2*t*cos((1.0/3)*phi); // *2
} else {
double Q = cbrt(D1 + sqrt(D)); // *2
St = Q - D0 / Q; // *2
}
double p = 3*cc; // *-2
double SS = (1.0/3)*(p + St); // *4
double S = sqrt(SS); // *2
double q = 2*cc*c + 4*d; // *2
double l = sqrt(p - SS + q / S) - S - c; // *2
double ll = l*l; // *4
double ll4 = ll + 4; // *4
double esin = (4*l) / ll4;
double ecos = (4 - ll) / ll4;
if (switched) {
double t = esin;
esin = ecos;
ecos = t;
}
*ecos_ret = copysign(ecos, a*x);
*esin_ret = copysign(esin, b*y);
}
Try it online!
You just need to calculate the intersection of the line [P1,P0] to your elipse which is S1.
If the line equeation is:
and the elipse equesion is:
than the values of S1 will be:
Now you just need to calculate the distance between S1 to P1 , the formula (for A,B points) is:
I've solved the distance issue via focal points.
For every point on the ellipse
r1 + r2 = 2*a0
where
r1 - Euclidean distance from the given point to focal point 1
r2 - Euclidean distance from the given point to focal point 2
a0 - semimajor axis length
I can also calculate the r1 and r2 for any given point which gives me another ellipse that this point lies on that is concentric to the given ellipse. So the distance is
d = Abs((r1 + r2) / 2 - a0)
As propposed by user3235832
you shall solve quartic equation to find the normal to the ellipse (https://www.mathpages.com/home/kmath505/kmath505.htm). With good initial value only few iterations are needed (I use it myself). As an initial value I use S1 from your picture.
The fastest method I guess is
http://wwwf.imperial.ac.uk/~rn/distance2ellipse.pdf
Which has been mentioned also by Matt but as he found out the method doesn't work very well inside of ellipse.
The problem is the theta initialization.
I proposed an stable initialization:
Find the intersection of ellipse and horizontal line passing the point.
Find the other intersection using vertical line.
Choose the one that is closer the point.
Calculate the initial angle based on that point.
I got good results with no issue inside and outside:
As you can see in the following image it just iterated about 3 times to reach 1e-8. Close to axis it is 1 iteration.
The C++ code is here:
double initialAngle(double a, double b, double x, double y) {
auto abs_x = fabs(x);
auto abs_y = fabs(y);
bool isOutside = false;
if (abs_x > a || abs_y > b) isOutside = true;
double xd, yd;
if (!isOutside) {
xd = sqrt((1.0 - y * y / (b * b)) * (a * a));
if (abs_x > xd)
isOutside = true;
else {
yd = sqrt((1.0 - x * x / (a * a)) * (b * b));
if (abs_y > yd)
isOutside = true;
}
}
double t;
if (isOutside)
t = atan2(a * y, b * x); //The point is outside of ellipse
else {
//The point is inside
if (xd < yd) {
if (x < 0) xd = -xd;
t = atan2(y, xd);
}
else {
if (y < 0) yd = -yd;
t = atan2(yd, x);
}
}
return t;
}
double distanceToElipse(double a, double b, double x, double y, int maxIter = 10, double maxError = 1e-5) {
//std::cout <<"p="<< x << "," << y << std::endl;
auto a2mb2 = a * a - b * b;
double t = initialAngle(a, b, x, y);
auto ct = cos(t);
auto st = sin(t);
int i;
double err;
for (i = 0; i < maxIter; i++) {
auto f = a2mb2 * ct * st - x * a * st + y * b * ct;
auto fp = a2mb2 * (ct * ct - st * st) - x * a * ct - y * b * st;
auto t2 = t - f / fp;
err = fabs(t2 - t);
//std::cout << i + 1 << " " << err << std::endl;
t = t2;
ct = cos(t);
st = sin(t);
if (err < maxError) break;
}
auto dx = a * ct - x;
auto dy = b * st - y;
//std::cout << a * ct << "," << b * st << std::endl;
return sqrt(dx * dx + dy * dy);
}