我需要一个基本函数来求点到线段的最短距离。你可以随意用任何你想要的语言来编写解决方案;我可以把它翻译成什么我正在使用(Javascript)。

编辑:线段由两个端点定义。线段AB由两点A (x1,y1)和B (x2,y2)定义。我要求的是这条线段到点C (x3,y3)的距离。我的几何技能生疏了,所以我看到的例子让我很困惑,我很遗憾地承认。


当前回答

下面是devnullicus转换为c#的c++版本。对于我的实现,我需要知道交叉点,并找到他的解决方案。

public static bool PointSegmentDistanceSquared(PointF point, PointF lineStart, PointF lineEnd, out double distance, out PointF intersectPoint)
{
    const double kMinSegmentLenSquared = 0.00000001; // adjust to suit.  If you use float, you'll probably want something like 0.000001f
    const double kEpsilon = 1.0E-14; // adjust to suit.  If you use floats, you'll probably want something like 1E-7f
    double dX = lineEnd.X - lineStart.X;
    double dY = lineEnd.Y - lineStart.Y;
    double dp1X = point.X - lineStart.X;
    double dp1Y = point.Y - lineStart.Y;
    double segLenSquared = (dX * dX) + (dY * dY);
    double t = 0.0;

    if (segLenSquared >= -kMinSegmentLenSquared && segLenSquared <= kMinSegmentLenSquared)
    {
        // segment is a point.
        intersectPoint = lineStart;
        t = 0.0;
        distance = ((dp1X * dp1X) + (dp1Y * dp1Y));
    }
    else
    {
        // Project a line from p to the segment [p1,p2].  By considering the line
        // extending the segment, parameterized as p1 + (t * (p2 - p1)),
        // we find projection of point p onto the line. 
        // It falls where t = [(p - p1) . (p2 - p1)] / |p2 - p1|^2
        t = ((dp1X * dX) + (dp1Y * dY)) / segLenSquared;
        if (t < kEpsilon)
        {
            // intersects at or to the "left" of first segment vertex (lineStart.X, lineStart.Y).  If t is approximately 0.0, then
            // intersection is at p1.  If t is less than that, then there is no intersection (i.e. p is not within
            // the 'bounds' of the segment)
            if (t > -kEpsilon)
            {
                // intersects at 1st segment vertex
                t = 0.0;
            }
            // set our 'intersection' point to p1.
            intersectPoint = lineStart;
            // Note: If you wanted the ACTUAL intersection point of where the projected lines would intersect if
            // we were doing PointLineDistanceSquared, then intersectPoint.X would be (lineStart.X + (t * dx)) and intersectPoint.Y would be (lineStart.Y + (t * dy)).
        }
        else if (t > (1.0 - kEpsilon))
        {
            // intersects at or to the "right" of second segment vertex (lineEnd.X, lineEnd.Y).  If t is approximately 1.0, then
            // intersection is at p2.  If t is greater than that, then there is no intersection (i.e. p is not within
            // the 'bounds' of the segment)
            if (t < (1.0 + kEpsilon))
            {
                // intersects at 2nd segment vertex
                t = 1.0;
            }
            // set our 'intersection' point to p2.
            intersectPoint = lineEnd;
            // Note: If you wanted the ACTUAL intersection point of where the projected lines would intersect if
            // we were doing PointLineDistanceSquared, then intersectPoint.X would be (lineStart.X + (t * dx)) and intersectPoint.Y would be (lineStart.Y + (t * dy)).
        }
        else
        {
            // The projection of the point to the point on the segment that is perpendicular succeeded and the point
            // is 'within' the bounds of the segment.  Set the intersection point as that projected point.
            intersectPoint = new PointF((float)(lineStart.X + (t * dX)), (float)(lineStart.Y + (t * dY)));
        }
        // return the squared distance from p to the intersection point.  Note that we return the squared distance
        // as an optimization because many times you just need to compare relative distances and the squared values
        // works fine for that.  If you want the ACTUAL distance, just take the square root of this value.
        double dpqX = point.X - intersectPoint.X;
        double dpqY = point.Y - intersectPoint.Y;

        distance = ((dpqX * dpqX) + (dpqY * dpqY));
    }

    return true;
}

其他回答

在f#中,点c到a和b之间的线段的距离为:

let pointToLineSegmentDistance (a: Vector, b: Vector) (c: Vector) =
  let d = b - a
  let s = d.Length
  let lambda = (c - a) * d / s
  let p = (lambda |> max 0.0 |> min s) * d / s
  (a + p - c).Length

向量d沿着线段从a指向b。d/s与c-a的点积给出了无限直线与点c之间最接近点的参数。使用min和max函数将该参数钳制到范围0..s,使该点位于a和b之间。最后,a+p-c的长度是c到线段上最近点的距离。

使用示例:

pointToLineSegmentDistance (Vector(0.0, 0.0), Vector(1.0, 0.0)) (Vector(-1.0, 1.0))

I'm assuming you want to find the shortest distance between the point and a line segment; to do this, you need to find the line (lineA) which is perpendicular to your line segment (lineB) which goes through your point, determine the intersection between that line (lineA) and your line which goes through your line segment (lineB); if that point is between the two points of your line segment, then the distance is the distance between your point and the point you just found which is the intersection of lineA and lineB; if the point is not between the two points of your line segment, you need to get the distance between your point and the closer of two ends of the line segment; this can be done easily by taking the square distance (to avoid a square root) between the point and the two points of the line segment; whichever is closer, take the square root of that one.

在javascript中使用几何:

var a = { x:20, y:20};//start segment    
var b = { x:40, y:30};//end segment   
var c = { x:37, y:14};//point   

// magnitude from a to c    
var ac = Math.sqrt( Math.pow( ( a.x - c.x ), 2 ) + Math.pow( ( a.y - c.y ), 2) );    
// magnitude from b to c   
var bc = Math.sqrt( Math.pow( ( b.x - c.x ), 2 ) + Math.pow( ( b.y - c.y ), 2 ) );    
// magnitude from a to b (base)     
var ab = Math.sqrt( Math.pow( ( a.x - b.x ), 2 ) + Math.pow( ( a.y - b.y ), 2 ) );    
 // perimeter of triangle     
var p = ac + bc + ab;    
 // area of the triangle    
var area = Math.sqrt( p/2 * ( p/2 - ac) * ( p/2 - bc ) * ( p/2 - ab ) );    
 // height of the triangle = distance    
var h = ( area * 2 ) / ab;    
console.log ("height: " + h);

这是一个为有限线段而做的实现,而不是像这里的大多数其他函数那样的无限线(这就是为什么我做这个)。

Paul Bourke的理论实施。

Python:

def dist(x1, y1, x2, y2, x3, y3): # x3,y3 is the point
    px = x2-x1
    py = y2-y1

    norm = px*px + py*py

    u =  ((x3 - x1) * px + (y3 - y1) * py) / float(norm)

    if u > 1:
        u = 1
    elif u < 0:
        u = 0

    x = x1 + u * px
    y = y1 + u * py

    dx = x - x3
    dy = y - y3

    # Note: If the actual distance does not matter,
    # if you only want to compare what this function
    # returns to other results of this function, you
    # can just return the squared distance instead
    # (i.e. remove the sqrt) to gain a little performance

    dist = (dx*dx + dy*dy)**.5

    return dist

AS3:

public static function segmentDistToPoint(segA:Point, segB:Point, p:Point):Number
{
    var p2:Point = new Point(segB.x - segA.x, segB.y - segA.y);
    var something:Number = p2.x*p2.x + p2.y*p2.y;
    var u:Number = ((p.x - segA.x) * p2.x + (p.y - segA.y) * p2.y) / something;

    if (u > 1)
        u = 1;
    else if (u < 0)
        u = 0;

    var x:Number = segA.x + u * p2.x;
    var y:Number = segA.y + u * p2.y;

    var dx:Number = x - p.x;
    var dy:Number = y - p.y;

    var dist:Number = Math.sqrt(dx*dx + dy*dy);

    return dist;
}

Java

private double shortestDistance(float x1,float y1,float x2,float y2,float x3,float y3)
    {
        float px=x2-x1;
        float py=y2-y1;
        float temp=(px*px)+(py*py);
        float u=((x3 - x1) * px + (y3 - y1) * py) / (temp);
        if(u>1){
            u=1;
        }
        else if(u<0){
            u=0;
        }
        float x = x1 + u * px;
        float y = y1 + u * py;

        float dx = x - x3;
        float dy = y - y3;
        double dist = Math.sqrt(dx*dx + dy*dy);
        return dist;

    }

2D坐标数组的Python Numpy实现:

import numpy as np


def dist2d(p1, p2, coords):
    ''' Distance from points to a finite line btwn p1 -> p2 '''
    assert coords.ndim == 2 and coords.shape[1] == 2, 'coords is not 2 dim'
    dp = p2 - p1
    st = dp[0]**2 + dp[1]**2
    u = ((coords[:, 0] - p1[0]) * dp[0] + (coords[:, 1] - p1[1]) * dp[1]) / st

    u[u > 1.] = 1.
    u[u < 0.] = 0.

    dx = (p1[0] + u * dp[0]) - coords[:, 0]
    dy = (p1[1] + u * dp[1]) - coords[:, 1]

    return np.sqrt(dx**2 + dy**2)


# Usage:
p1 = np.array([0., 0.])
p2 = np.array([0., 10.])

# List of coordinates
coords = np.array(
    [[0., 0.],
     [5., 5.],
     [10., 10.],
     [20., 20.]
     ])

d = dist2d(p1, p2, coords)

# Single coordinate
coord = np.array([25., 25.])
d = dist2d(p1, p2, coord[np.newaxis, :])