上面有很多解决方案，但我认为下面的解决方案很简单，很容易理解。

矢量AB和矢量CD相交当且仅当

端点a和b在线段CD的两边。 端点c和d在线段AB的对边。

更具体地说，a和b在线段CD的对面当且仅当两个三元组中有一个是逆时针顺序的。

Intersect(a, b, c, d)
 if CCW(a, c, d) == CCW(b, c, d)
    return false;
 else if CCW(a, b, c) == CCW(a, b, d)
    return false;
 else
    return true;

这里的CCW代表逆时针，根据点的方向返回真/假。

来源:http://compgeom.cs.uiuc.edu/~jeffe/teaching/373/notes/x06-sweepline.pdf 第二页

曾经在这里被接受的答案是不正确的(它已经被不接受了，所以万岁!)它不能正确地消除所有非交点。简单地说，它可能有效，但也可能失败，特别是在0和1被认为对h有效的情况下。

考虑以下情况:

直线(4,1)-(5,1)和(0,0)-(0,2)

这两条垂线显然不重叠。

= (4,1) B =(5、1) C = (0, 0) D = (0, 2) E = (1) - (4,1) = (1,0) F = (0, 2) - (0, 0) = (0, 2) P = (0, 1) h =((4,1) -(0, 0))点(0,1)/((0,2)点(0,1))= 0

根据上面的答案，这两条线段在端点处相遇(值为0和1)。该端点为:

(0, 0) + (0, 2) * 0 = (0, 0)

So, apparently the two line segments meet at (0,0), which is on line CD, but not on line AB. So what is going wrong? The answer is that the values of 0 and 1 are not valid and only sometimes HAPPEN to correctly predict endpoint intersection. When the extension of one line (but not the other) would meet the line segment, the algorithm predicts an intersection of line segments, but this is not correct. I imagine that by testing starting with AB vs CD and then also testing with CD vs AB, this problem would be eliminated. Only if both fall between 0 and 1 inclusively can they be said to intersect.

如果你必须预测端点，我建议使用向量叉乘法。

-Dan

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

根据t3chb0t的答案:

int intersezione_linee(int x1, int y1, int x2, int y2, int x3, int y3, int x4, int y4, int& p_x, int& p_y)
{
   //L1: estremi (x1,y1)(x2,y2) L2: estremi (x3,y3)(x3,y3)
   int d;
   d = (x1-x2)*(y3-y4) - (y1-y2)*(x3-x4);
   if(!d)
       return 0;
   p_x = ((x1*y2-y1*x2)*(x3-x4) - (x1-x2)*(x3*y4-y3*x4))/d;
   p_y = ((x1*y2-y1*x2)*(y3-y4) - (y1-y2)*(x3*y4-y3*x4))/d;
   return 1;
}

int in_bounding_box(int x1, int y1, int x2, int y2, int p_x, int p_y)
{
    return p_x>=x1 && p_x<=x2 && p_y>=y1 && p_y<=y2;

}

int intersezione_segmenti(int x1, int y1, int x2, int y2, int x3, int y3, int x4, int y4, int& p_x, int& p_y)
{
    if (!intersezione_linee(x1,y1,x2,y2,x3,y3,x4,y4,p_x,p_y))
        return 0;

    return in_bounding_box(x1,y1,x2,y2,p_x,p_y) && in_bounding_box(x3,y3,x4,y4,p_x,p_y);
}

我从《多视图几何》这本书里读到了这些算法

以下文本使用

'作为转置符号

*作为点积

当用作算子时，X作为叉乘

1. 线的定义

点x_vec = (x, y)'在直线ax + by + c = 0上

标记L = (a, b, c)'，点为(x, y, 1)'为齐次坐标

直线方程可以写成

(x, y, 1)(a, b, c)' = 0或x' * L = 0

2. 直线交点

我们有两条直线L1=(a1, b1, c1)'， L2=(a2, b2, c2)'

假设x是一个点，一个向量，x = L1 x L2 (L1叉乘L2)。

注意，x始终是一个二维点，如果你对(L1xL2)是一个三元素向量，x是一个二维坐标感到困惑，请阅读齐次坐标。

根据三重积，我们知道

L1 * (L1 x L2) = 0, L2 * (L1 x L2) = 0，因为L1,L2共平面

我们用向量x代替L1*x，那么L1*x=0, L2*x=0，这意味着x在L1和L2上，x是交点。

注意，这里x是齐次坐标，如果x的最后一个元素是零，这意味着L1和L2是平行的。

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