我已经尝试实现上述Jason所描述的算法;不幸的是，虽然在调试数学工作，我发现许多情况下，它不起作用。

例如，考虑点A(10,10) B(20,20) C(10,1) D(1,10) h=。5然而，通过检查可以清楚地看到，这些部分彼此一点也不接近。

将其绘制成图可以清楚地看出，0 < h < 1条件仅表明如果存在截距点，则截距点将位于CD上，而不告诉我们该点是否位于AB上。 为了确保有一个交叉点，你必须对变量g进行对称计算，拦截的要求是: 0 < g < 1 AND 0 < h < 1

只是想提一下，一个很好的解释和明确的解决方案可以在数字食谱系列中找到。我有这本书的第三版，答案在1117页21.4节。另一种不同命名的解决方案可以在玛丽娜·加夫里洛娃(Marina Gavrilova)的论文中找到。在我看来，她的解决办法要简单一些。

我的实现如下:

bool NuGeometry::IsBetween(const double& x0, const double& x, const double& x1){
   return (x >= x0) && (x <= x1);
}

bool NuGeometry::FindIntersection(const double& x0, const double& y0, 
     const double& x1, const double& y1,
     const double& a0, const double& b0, 
     const double& a1, const double& b1, 
     double& xy, double& ab) {
   // four endpoints are x0, y0 & x1,y1 & a0,b0 & a1,b1
   // returned values xy and ab are the fractional distance along xy and ab
   // and are only defined when the result is true

   bool partial = false;
   double denom = (b0 - b1) * (x0 - x1) - (y0 - y1) * (a0 - a1);
   if (denom == 0) {
      xy = -1;
      ab = -1;
   } else {
      xy = (a0 * (y1 - b1) + a1 * (b0 - y1) + x1 * (b1 - b0)) / denom;
      partial = NuGeometry::IsBetween(0, xy, 1);
      if (partial) {
         // no point calculating this unless xy is between 0 & 1
         ab = (y1 * (x0 - a1) + b1 * (x1 - x0) + y0 * (a1 - x1)) / denom; 
      }
   }
   if ( partial && NuGeometry::IsBetween(0, ab, 1)) {
      ab = 1-ab;
      xy = 1-xy;
      return true;
   }  else return false;
}

如果矩形的每条边都是一条线段，并且用户绘制的部分也是一条线段，那么您只需检查用户绘制的线段是否与四条边线段相交。这应该是一个相当简单的练习，给定每个段的起点和终点。

基于@Gareth Rees的回答，Python版本:

import numpy as np

def np_perp( a ) :
    b = np.empty_like(a)
    b[0] = a[1]
    b[1] = -a[0]
    return b

def np_cross_product(a, b):
    return np.dot(a, np_perp(b))

def np_seg_intersect(a, b, considerCollinearOverlapAsIntersect = False):
    # https://stackoverflow.com/questions/563198/how-do-you-detect-where-two-line-segments-intersect/565282#565282
    # http://www.codeproject.com/Tips/862988/Find-the-intersection-point-of-two-line-segments
    r = a[1] - a[0]
    s = b[1] - b[0]
    v = b[0] - a[0]
    num = np_cross_product(v, r)
    denom = np_cross_product(r, s)
    # If r x s = 0 and (q - p) x r = 0, then the two lines are collinear.
    if np.isclose(denom, 0) and np.isclose(num, 0):
        # 1. If either  0 <= (q - p) * r <= r * r or 0 <= (p - q) * s <= * s
        # then the two lines are overlapping,
        if(considerCollinearOverlapAsIntersect):
            vDotR = np.dot(v, r)
            aDotS = np.dot(-v, s)
            if (0 <= vDotR  and vDotR <= np.dot(r,r)) or (0 <= aDotS  and aDotS <= np.dot(s,s)):
                return True
        # 2. If neither 0 <= (q - p) * r = r * r nor 0 <= (p - q) * s <= s * s
        # then the two lines are collinear but disjoint.
        # No need to implement this expression, as it follows from the expression above.
        return None
    if np.isclose(denom, 0) and not np.isclose(num, 0):
        # Parallel and non intersecting
        return None
    u = num / denom
    t = np_cross_product(v, s) / denom
    if u >= 0 and u <= 1 and t >= 0 and t <= 1:
        res = b[0] + (s*u)
        return res
    # Otherwise, the two line segments are not parallel but do not intersect.
    return None

人们似乎对Gavin的答案很感兴趣，cortijon在评论中提出了一个javascript版本，iMalc提供了一个计算量略少的版本。一些人指出了各种代码建议的缺点，另一些人则评论了一些代码建议的效率。

iMalc通过Gavin的答案提供的算法是我目前在一个javascript项目中使用的算法，我只是想在这里提供一个清理过的版本，如果它可以帮助到任何人的话。

// Some variables for reuse, others may do this differently
var p0x, p1x, p2x, p3x, ix,
    p0y, p1y, p2y, p3y, iy,
    collisionDetected;

// do stuff, call other functions, set endpoints...

// note: for my purpose I use |t| < |d| as opposed to
// |t| <= |d| which is equivalent to 0 <= t < 1 rather than
// 0 <= t <= 1 as in Gavin's answer - results may vary

var lineSegmentIntersection = function(){
    var d, dx1, dx2, dx3, dy1, dy2, dy3, s, t;

    dx1 = p1x - p0x;      dy1 = p1y - p0y;
    dx2 = p3x - p2x;      dy2 = p3y - p2y;
    dx3 = p0x - p2x;      dy3 = p0y - p2y;

    collisionDetected = 0;

    d = dx1 * dy2 - dx2 * dy1;

    if(d !== 0){
        s = dx1 * dy3 - dx3 * dy1;
        if((s <= 0 && d < 0 && s >= d) || (s >= 0 && d > 0 && s <= d)){
            t = dx2 * dy3 - dx3 * dy2;
            if((t <= 0 && d < 0 && t > d) || (t >= 0 && d > 0 && t < d)){
                t = t / d;
                collisionDetected = 1;
                ix = p0x + t * dx1;
                iy = p0y + t * dy1;
            }
        }
    }
};

iMalc回答的Python版本:

def find_intersection( p0, p1, p2, p3 ) :

    s10_x = p1[0] - p0[0]
    s10_y = p1[1] - p0[1]
    s32_x = p3[0] - p2[0]
    s32_y = p3[1] - p2[1]

    denom = s10_x * s32_y - s32_x * s10_y

    if denom == 0 : return None # collinear

    denom_is_positive = denom > 0

    s02_x = p0[0] - p2[0]
    s02_y = p0[1] - p2[1]

    s_numer = s10_x * s02_y - s10_y * s02_x

    if (s_numer < 0) == denom_is_positive : return None # no collision

    t_numer = s32_x * s02_y - s32_y * s02_x

    if (t_numer < 0) == denom_is_positive : return None # no collision

    if (s_numer > denom) == denom_is_positive or (t_numer > denom) == denom_is_positive : return None # no collision


    # collision detected

    t = t_numer / denom

    intersection_point = [ p0[0] + (t * s10_x), p0[1] + (t * s10_y) ]


    return intersection_point