Is there an easy way to determine if a point is inside a triangle? It's 2D, not 3D.
25 Answers
In general, the simplest (and quite optimal) algorithm is checking on which side of the half-plane created by the edges the point is.
Here's some high quality info in this topic on GameDev, including performance issues.
And here's some code to get you started:
float sign (fPoint p1, fPoint p2, fPoint p3)
{
return (p1.x - p3.x) * (p2.y - p3.y) - (p2.x - p3.x) * (p1.y - p3.y);
}
bool PointInTriangle (fPoint pt, fPoint v1, fPoint v2, fPoint v3)
{
float d1, d2, d3;
bool has_neg, has_pos;
d1 = sign(pt, v1, v2);
d2 = sign(pt, v2, v3);
d3 = sign(pt, v3, v1);
has_neg = (d1 < 0) || (d2 < 0) || (d3 < 0);
has_pos = (d1 > 0) || (d2 > 0) || (d3 > 0);
return !(has_neg && has_pos);
}
Solve the following equation system:
p = p0 + (p1 - p0) * s + (p2 - p0) * t
The point p is inside the triangle if 0 <= s <= 1 and 0 <= t <= 1 and s + t <= 1.
s,t and 1 - s - t are called the barycentric coordinates of the point p.
I wrote this code before a final attempt with Google and finding this page, so I thought I'd share it. It is basically an optimized version of Kisielewicz answer. I looked into the Barycentric method also but judging from the Wikipedia article I have a hard time seeing how it is more efficient (I'm guessing there is some deeper equivalence). Anyway, this algorithm has the advantage of not using division; a potential problem is the behavior of the edge detection depending on orientation.
bool intpoint_inside_trigon(intPoint s, intPoint a, intPoint b, intPoint c)
{
int as_x = s.x-a.x;
int as_y = s.y-a.y;
bool s_ab = (b.x-a.x)*as_y-(b.y-a.y)*as_x > 0;
if((c.x-a.x)*as_y-(c.y-a.y)*as_x > 0 == s_ab) return false;
if((c.x-b.x)*(s.y-b.y)-(c.y-b.y)*(s.x-b.x) > 0 != s_ab) return false;
return true;
}
In words, the idea is this: Is the point s to the left of or to the right of both the lines AB and AC? If true, it can't be inside. If false, it is at least inside the "cones" that satisfy the condition. Now since we know that a point inside a trigon (triangle) must be to the same side of AB as BC (and also CA), we check if they differ. If they do, s can't possibly be inside, otherwise s must be inside.
Some keywords in the calculations are line half-planes and the determinant (2x2 cross product). Perhaps a more pedagogical way is probably to think of it as a point being inside iff it's to the same side (left or right) to each of the lines AB, BC and CA. The above way seemed a better fit for some optimization however.
A simple way is to:
find the vectors connecting the point to each of the triangle's three vertices and sum the angles between those vectors. If the sum of the angles is 2*pi then the point is inside the triangle.
Two good sites that explain alternatives are:
Here is a solution in python that is efficient, documented and contains three unittests. It's professional-grade quality and ready to be dropped into your project in the form of a module as is.
import unittest
###############################################################################
def point_in_triangle(point, triangle):
"""Returns True if the point is inside the triangle
and returns False if it falls outside.
- The argument *point* is a tuple with two elements
containing the X,Y coordinates respectively.
- The argument *triangle* is a tuple with three elements each
element consisting of a tuple of X,Y coordinates.
It works like this:
Walk clockwise or counterclockwise around the triangle
and project the point onto the segment we are crossing
by using the dot product.
Finally, check that the vector created is on the same side
for each of the triangle's segments.
"""
# Unpack arguments
x, y = point
ax, ay = triangle[0]
bx, by = triangle[1]
cx, cy = triangle[2]
# Segment A to B
side_1 = (x - bx) * (ay - by) - (ax - bx) * (y - by)
# Segment B to C
side_2 = (x - cx) * (by - cy) - (bx - cx) * (y - cy)
# Segment C to A
side_3 = (x - ax) * (cy - ay) - (cx - ax) * (y - ay)
# All the signs must be positive or all negative
return (side_1 < 0.0) == (side_2 < 0.0) == (side_3 < 0.0)
###############################################################################
class TestPointInTriangle(unittest.TestCase):
triangle = ((22 , 8),
(12 , 55),
(7 , 19))
def test_inside(self):
point = (15, 20)
self.assertTrue(point_in_triangle(point, self.triangle))
def test_outside(self):
point = (1, 7)
self.assertFalse(point_in_triangle(point, self.triangle))
def test_border_case(self):
"""If the point is exactly on one of the triangle's edges,
we consider it is inside."""
point = (7, 19)
self.assertTrue(point_in_triangle(point, self.triangle))
###############################################################################
if __name__ == "__main__":
suite = unittest.defaultTestLoader.loadTestsFromTestCase(TestPointInTriangle)
unittest.TextTestRunner().run(suite)
There is an additional optional graphical test for the algorithm above to confirm its validity:
import random
from matplotlib import pyplot
from triangle_test import point_in_triangle
###############################################################################
# The area #
size_x = 64
size_y = 64
# The triangle #
triangle = ((22 , 8),
(12 , 55),
(7 , 19))
# Number of random points #
count_points = 10000
# Prepare the figure #
figure = pyplot.figure()
axes = figure.add_subplot(111, aspect='equal')
axes.set_title("Test the 'point_in_triangle' function")
axes.set_xlim(0, size_x)
axes.set_ylim(0, size_y)
# Plot the triangle #
from matplotlib.patches import Polygon
axes.add_patch(Polygon(triangle, linewidth=1, edgecolor='k', facecolor='none'))
# Plot the points #
for i in range(count_points):
x = random.uniform(0, size_x)
y = random.uniform(0, size_y)
if point_in_triangle((x,y), triangle): pyplot.plot(x, y, '.g')
else: pyplot.plot(x, y, '.b')
# Save it #
figure.savefig("point_in_triangle.pdf")
Producing the following graphic:
This is the simplest concept to determine if a point is inside or outside the triangle or on an arm of a triangle.
Determination of a point is inside a triangle by determinants:
The simplest working code:
#-*- coding: utf-8 -*-
import numpy as np
tri_points = [(1,1),(2,3),(3,1)]
def pisinTri(point,tri_points):
Dx , Dy = point
A,B,C = tri_points
Ax, Ay = A
Bx, By = B
Cx, Cy = C
M1 = np.array([ [Dx - Bx, Dy - By, 0],
[Ax - Bx, Ay - By, 0],
[1 , 1 , 1]
])
M2 = np.array([ [Dx - Ax, Dy - Ay, 0],
[Cx - Ax, Cy - Ay, 0],
[1 , 1 , 1]
])
M3 = np.array([ [Dx - Cx, Dy - Cy, 0],
[Bx - Cx, By - Cy, 0],
[1 , 1 , 1]
])
M1 = np.linalg.det(M1)
M2 = np.linalg.det(M2)
M3 = np.linalg.det(M3)
print(M1,M2,M3)
if(M1 == 0 or M2 == 0 or M3 ==0):
print("Point: ",point," lies on the arms of Triangle")
elif((M1 > 0 and M2 > 0 and M3 > 0)or(M1 < 0 and M2 < 0 and M3 < 0)):
#if products is non 0 check if all of their sign is same
print("Point: ",point," lies inside the Triangle")
else:
print("Point: ",point," lies outside the Triangle")
print("Vertices of Triangle: ",tri_points)
points = [(0,0),(1,1),(2,3),(3,1),(2,2),(4,4),(1,0),(0,4)]
for c in points:
pisinTri(c,tri_points)
Other function in python, faster than Developer's method (for me at least) and inspired by Cédric Dufour solution:
def ptInTriang(p_test, p0, p1, p2):
dX = p_test[0] - p0[0]
dY = p_test[1] - p0[1]
dX20 = p2[0] - p0[0]
dY20 = p2[1] - p0[1]
dX10 = p1[0] - p0[0]
dY10 = p1[1] - p0[1]
s_p = (dY20*dX) - (dX20*dY)
t_p = (dX10*dY) - (dY10*dX)
D = (dX10*dY20) - (dY10*dX20)
if D > 0:
return ( (s_p >= 0) and (t_p >= 0) and (s_p + t_p) <= D )
else:
return ( (s_p <= 0) and (t_p <= 0) and (s_p + t_p) >= D )
You can test it with:
X_size = 64
Y_size = 64
ax_x = np.arange(X_size).astype(np.float32)
ax_y = np.arange(Y_size).astype(np.float32)
coords=np.meshgrid(ax_x,ax_y)
points_unif = (coords[0].reshape(X_size*Y_size,),coords[1].reshape(X_size*Y_size,))
p_test = np.array([0 , 0])
p0 = np.array([22 , 8])
p1 = np.array([12 , 55])
p2 = np.array([7 , 19])
fig = plt.figure(dpi=300)
for i in range(0,X_size*Y_size):
p_test[0] = points_unif[0][i]
p_test[1] = points_unif[1][i]
if ptInTriang(p_test, p0, p1, p2):
plt.plot(p_test[0], p_test[1], '.g')
else:
plt.plot(p_test[0], p_test[1], '.r')
It takes a lot to plot, but that grid is tested in 0.0195319652557 seconds against 0.0844349861145 seconds of Developer's code.
Finally the code comment:
# Using barycentric coordintes, any point inside can be described as:
# X = p0.x * r + p1.x * s + p2.x * t
# Y = p0.y * r + p1.y * s + p2.y * t
# with:
# r + s + t = 1 and 0 < r,s,t < 1
# then: r = 1 - s - t
# and then:
# X = p0.x * (1 - s - t) + p1.x * s + p2.x * t
# Y = p0.y * (1 - s - t) + p1.y * s + p2.y * t
#
# X = p0.x + (p1.x-p0.x) * s + (p2.x-p0.x) * t
# Y = p0.y + (p1.y-p0.y) * s + (p2.y-p0.y) * t
#
# X - p0.x = (p1.x-p0.x) * s + (p2.x-p0.x) * t
# Y - p0.y = (p1.y-p0.y) * s + (p2.y-p0.y) * t
#
# we have to solve:
#
# [ X - p0.x ] = [(p1.x-p0.x) (p2.x-p0.x)] * [ s ]
# [ Y - p0.Y ] [(p1.y-p0.y) (p2.y-p0.y)] [ t ]
#
# ---> b = A*x ; ---> x = A^-1 * b
#
# [ s ] = A^-1 * [ X - p0.x ]
# [ t ] [ Y - p0.Y ]
#
# A^-1 = 1/D * adj(A)
#
# The adjugate of A:
#
# adj(A) = [(p2.y-p0.y) -(p2.x-p0.x)]
# [-(p1.y-p0.y) (p1.x-p0.x)]
#
# The determinant of A:
#
# D = (p1.x-p0.x)*(p2.y-p0.y) - (p1.y-p0.y)*(p2.x-p0.x)
#
# Then:
#
# s_p = { (p2.y-p0.y)*(X - p0.x) - (p2.x-p0.x)*(Y - p0.Y) }
# t_p = { (p1.x-p0.x)*(Y - p0.Y) - (p1.y-p0.y)*(X - p0.x) }
#
# s = s_p / D
# t = t_p / D
#
# Recovering r:
#
# r = 1 - (s_p + t_p)/D
#
# Since we only want to know if it is insidem not the barycentric coordinate:
#
# 0 < 1 - (s_p + t_p)/D < 1
# 0 < (s_p + t_p)/D < 1
# 0 < (s_p + t_p) < D
#
# The condition is:
# if D > 0:
# s_p > 0 and t_p > 0 and (s_p + t_p) < D
# else:
# s_p < 0 and t_p < 0 and (s_p + t_p) > D
#
# s_p = { dY20*dX - dX20*dY }
# t_p = { dX10*dY - dY10*dX }
# D = dX10*dY20 - dY10*dX20
One of the easiest ways to check if the area formed by the vertices of triangle (x1,y1),(x2,y2),(x3,y3) is positive or not.
Area can by calculated by the formula:
1/2 [x1(y2–y3) + x2(y3–y1) + x3(y1–y2)]
or python code can be written as:
def triangleornot(p1,p2,p3):
return (1/ 2) [p1[0](p2[1]–p3[1]) + p2[0] (p3[1]–p1[1]) + p3[0] (p1[0]–p2[0])]
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