用Matlab直接实现Grumdrig

function ans=distP2S(px,py,vx,vy,wx,wy)
% [px py vx vy wx wy]
  t=( (px-vx)*(wx-vx)+(py-vy)*(wy-vy) )/idist(vx,wx,vy,wy)^2;
  [idist(px,vx,py,vy) idist(px,vx+t*(wx-vx),py,vy+t*(wy-vy)) idist(px,wx,py,wy) ];
  ans(1+(t>0)+(t>1)); % <0 0<=t<=1 t>1     
 end

function d=idist(a,b,c,d)
 d=abs(a-b+1i*(c-d));
end

一个2D和3D的解决方案

考虑基底的变化，使得线段变成(0,0,0)-(d, 0,0)和点(u, v, 0)。在这个平面上，最短的距离由

    u ≤ 0 -> d(A, C)
0 ≤ u ≤ d -> |v|
d ≤ u     -> d(B, C)

(到其中一个端点或到支撑线的距离，取决于到该线的投影。等距轨迹由两个半圆和两条线段组成。)

式中，d为AB线段的长度，u、v分别为AB/d (AB方向的单位矢量)与AC的标量积和外积的模量。

AB.AC ≤ 0             -> |AC|
    0 ≤ AB.AC ≤ AB²   -> |ABxAC|/|AB|
          AB² ≤ AB.AC -> |BC|

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;

    }

伊莱，你选定的代码是错误的。在线段所在直线附近但远离线段一端的点将被错误地判断为接近线段。更新:上面提到的错误答案已不再被接受。

下面是一些正确的c++代码。它假设一个2d向量类vec2 {float x,y;}，本质上，带有加法、subract、缩放等运算符，以及一个距离和点积函数(即x1 x2 + y1 y2)。

float minimum_distance(vec2 v, vec2 w, vec2 p) {
  // Return minimum distance between line segment vw and point p
  const float l2 = length_squared(v, w);  // i.e. |w-v|^2 -  avoid a sqrt
  if (l2 == 0.0) return distance(p, v);   // v == w case
  // Consider the line extending the segment, parameterized as v + t (w - v).
  // We find projection of point p onto the line. 
  // It falls where t = [(p-v) . (w-v)] / |w-v|^2
  // We clamp t from [0,1] to handle points outside the segment vw.
  const float t = max(0, min(1, dot(p - v, w - v) / l2));
  const vec2 projection = v + t * (w - v);  // Projection falls on the segment
  return distance(p, projection);
}

编辑:我需要一个Javascript实现，所以在这里，没有依赖关系(或注释，但它是一个直接的端口以上)。点被表示为具有x和y属性的对象。

function sqr(x) { return x * x }
function dist2(v, w) { return sqr(v.x - w.x) + sqr(v.y - w.y) }
function distToSegmentSquared(p, v, w) {
  var l2 = dist2(v, w);
  if (l2 == 0) return dist2(p, v);
  var t = ((p.x - v.x) * (w.x - v.x) + (p.y - v.y) * (w.y - v.y)) / l2;
  t = Math.max(0, Math.min(1, t));
  return dist2(p, { x: v.x + t * (w.x - v.x),
                    y: v.y + t * (w.y - v.y) });
}
function distToSegment(p, v, w) { return Math.sqrt(distToSegmentSquared(p, v, w)); }

编辑2:我需要一个Java版本，但更重要的是，我需要3d版本而不是2d版本。

float dist_to_segment_squared(float px, float py, float pz, float lx1, float ly1, float lz1, float lx2, float ly2, float lz2) {
  float line_dist = dist_sq(lx1, ly1, lz1, lx2, ly2, lz2);
  if (line_dist == 0) return dist_sq(px, py, pz, lx1, ly1, lz1);
  float t = ((px - lx1) * (lx2 - lx1) + (py - ly1) * (ly2 - ly1) + (pz - lz1) * (lz2 - lz1)) / line_dist;
  t = constrain(t, 0, 1);
  return dist_sq(px, py, pz, lx1 + t * (lx2 - lx1), ly1 + t * (ly2 - ly1), lz1 + t * (lz2 - lz1));
}

这里，在函数参数中，<px,py,pz>是问题点，线段有端点<lx1,ly1,lz1>和<lx2,ly2,lz2>。函数dist_sq(假定存在)求两点之间距离的平方。

使用arctangents的一行解决方案:

思路是将A移动到(0,0)，并顺时针旋转三角形，使C位于X轴上， 当这种情况发生时，By就是距离。

a角= Atan(Cy - Ay, Cx - Ax); b角= Atan(By - Ay, Bx - Ax); AB长度=平方根((Bx - Ax)²+ (By - Ay)²) By = Sin (bAngle - aAngle) * ABLength

C#

public double Distance(Point a, Point b, Point c)
{
    // normalize points
    Point cn = new Point(c.X - a.X, c.Y - a.Y);
    Point bn = new Point(b.X - a.X, b.Y - a.Y);

    double angle = Math.Atan2(bn.Y, bn.X) - Math.Atan2(cn.Y, cn.X);
    double abLength = Math.Sqrt(bn.X*bn.X + bn.Y*bn.Y);

    return Math.Sin(angle)*abLength;
}

一行c#(要转换为SQL)

double distance = Math.Sin(Math.Atan2(b.Y - a.Y, b.X - a.X) - Math.Atan2(c.Y - a.Y, c.X - a.X)) * Math.Sqrt((b.X - a.X) * (b.X - a.X) + (b.Y - a.Y) * (b.Y - a.Y))

下面是HSQLDB的SQL实现:

CREATE FUNCTION dist_to_segment(px double, py double, vx double, vy double, wx double, wy double)
  RETURNS double
BEGIN atomic
   declare l2 double;
   declare t double;
   declare nx double;
   declare ny double;
   set l2 =(vx - wx)*(vx - wx) + (vy - wy)*(vy - wy);
   IF l2 = 0 THEN
     RETURN sqrt((vx - px)*(vx - px) + (vy - py)*(vy - py));
   ELSE
     set t = ((px - vx) * (wx - vx) + (py - vy) * (wy - vy)) / l2;
     set t = GREATEST(0, LEAST(1, t));
     set nx=vx + t * (wx - vx);
     set ny=vy + t * (wy - vy);
     RETURN sqrt((nx - px)*(nx - px) + (ny - py)*(ny - py));
   END IF;
END;

Postgres的实现:

CREATE FUNCTION dist_to_segment(px numeric, py numeric, vx numeric, vy numeric, wx numeric, wy numeric)
  RETURNS numeric
AS $$
   declare l2 numeric;
   declare t numeric;
   declare nx numeric;
   declare ny numeric;
BEGIN 
   l2 := (vx - wx)*(vx - wx) + (vy - wy)*(vy - wy);
   IF l2 = 0 THEN
     RETURN sqrt((vx - px)*(vx - px) + (vy - py)*(vy - py));
   ELSE
     t := ((px - vx) * (wx - vx) + (py - vy) * (wy - vy)) / l2;
     t := GREATEST(0, LEAST(1, t));
     nx := vx + t * (wx - vx);
     ny := vy + t * (wy - vy);
     RETURN sqrt((nx - px)*(nx - px) + (ny - py)*(ny - py));
   END IF;
END;
$$ LANGUAGE plpgsql;