Find the minimum area parallelogram enclosing all triangles - java

Following is the problem statement.
You have been given k number of equilateral triangles (There is a upper cap on
k, lets say k=<15). The triangles can be overlapping.
Now you have to find a parallelogram enclosing all the triangles and has the
minimum area. It is given that two opposite edges of the four edges are
parallel to either X axis or Y axis(That is your choice).
My Approach:
Let's say two of them are parallel to Y axis.
Then the leftmost point and the rightmost point of the set of triangles
will lie in two opposite edges of the parallelogram. Now I will draw two straight lines which pass through these points and are parallel to the Y axis.
This way I have found two edges its not so difficult.
Now I am stuck and don't know how to find other two.
I thought a lot but since I was unable to make it out I am posting it here.
Any help will be appreciated!!!!!!!

Build convex hull around all triangles vertices.
Then use rotating calipers to get a pair of parallel lines with the smallest vertical distance between them (parallelogram area is defined by height (here horizontal) - it is already fixed, and by vertical base length - choose minimum)

Related

Intersection between square shaped nodes and edges

I have a ŁŽquestion about the graphstream library
I want to write a program that counts the number of intersections between the nodes that are represented as a square with a specified size.
The main Problem is that, the nodes will be visualized as squares but if the coordinates of these nodes are just points x,y and here is exactly my Problem, because I want to check the intersections with the edges with the x,y coordinates but I can not do this properly!
because in some cases the corner of the square or its edges intersect with the edges but the original point that represents the square or the node in graphstream does not, I tried all the possible solutions with collinear points , slopes and everything but nothing worked for me, the question is, is there anyway in Grpahstream so that I can find out the coordinates of the edges or the corners of the square so that I can check with the line segment equation if they intersect ?
I mean something like that as shown in the picture
https://i.stack.imgur.com/PG4Dv.png
Best regards

Filling a 2D curved concave shape in libgdx

What are the approaches to color-filling a curved concave shape in libgdx?
Let us assume that:
1) The shape-to-be-rendered is built from an array of vertices that are close to each other.
2) Edges between the vertices are known.
3) The vertices' positions might dynamically change over time. We are guaranteed that no self-intersections will occur (and that the shape will not be hollow).
The right-most picture is what I'm trying to render in libgdx (with-or-without the outline).
From what I've read, triangulation is a popular approach to non-curved shapes, but in order for it look any good for shapes with curvature, I imagine we would need a huge number of vertices (so that the many lines "zoomed out" resemble a smooth curve).
Triangulatin is not the only one way to go with this. I am not familiar with your gfx lib but I would do this in low level:
Subdivide your polyline to set of convex ones
you need to know which segment is line and which is curve and for the curve you also need to know the control points from neighboring patch so the connection is smooth. The concave boundary can be detected by the fact that angle change swaps sign so if you got consequent points p(0)...p(n) with consistent widing rule then
d(i ) = p(i+1)-p(i )
d(i-1) = p(i )-p(i-1)
n(i) = cross( d(i) , d(i-1) )
n(i).z * n(i-1).z < 0.0
so the cross product will give you normal and if the direction of the normal swaps it mean the winding is changed... The equatio assumes points are in xy plane or parallel to it. If not the case the last line should be
dot( n(i) , n(i-1) ) < 0.0
if true p(i) is your concave boundary and you should split your shape by it
fill the polylines
you can use the same approach as for triangles or convex polygons see:
how to rasterize rotated rectangle
Algorithm to fill triangle
render polyline outline
Of coarse if you do not have fast pixel access or horizontal line rendering available is this not a good way to go. There is one simple but not as fast option:
render outline
flood fill inside
this step is slow which might cause problems for bigger resolutions.

Rotating line sweep - sorting edges

I'm trying to implement Lee's visibility graph.
There might be n number of polygons, where each side of the polygon is an edge. Let's say there is a point p1, and a half-liner parallel to the positive x-axis start at p1. I need to find edges that are intersected by r, and store them in sorted order.
An edge that is intersected first by line r has higher priority, also an edge that's closer has a higher priority, but when seen > distance.
E.g p1 = (0, 1), and a polygon with the following vertices {(2,
4),(3,6),(5, 20)}. The edges for this polygon should be sorted as
[((2, 4),(5, 20)), ((2,4),(3, 6)), ((3, 6),(5, 20))].
Hence, how can I sort these edges?
(if you go to the link and read that, I think you will have a better idea, sorry for my explanation).
My prime idea: sort them by distance and angel from p1 to the first Vertex of the edge encountered by r. Though, all vertices have more than one edge (since each vertex/edge is part of a polygon), and I don't know how to sort these two.
Any ideas or hints would be much appreciated.
Just some references:
https://taipanrex.github.io/2016/10/19/Distance-Tables-Part-2-Lees-Visibility-Graph-Algorithm.html
And a book: Computational Geometry ALgorithms and Application.
I found a way for those who are interested:
The sweep line is rotating anti-clockwise and its ordering edges based on taking measurements when it encounters the first vertice of that edge, which are: angle between the initial position of the half line (when it's parallel to positive x-axis) and the vertice encountered, the distance between p1 and the encountered vertice. The smaller the angle and distance the better, also angle has higher priority than distance.
I also take a 3rd measurement, since the half line rotates, when it reaches a vertice it should intersect it, hence I take the angle between the half line and the edge of the vertice. The large the angle the higher priority for this one, since it means the edge is closer. This angle is to differentiate between edges that have the same first encountered vertice by the half line. Therefore, the priority for this measurement is the lowest.
Hopefully, this will help someone.

Find intersection between Rectangle and Union of a set of rectangles?

I'm looking for a way to calculate the area of an intersection between a single rectangle and the union of a small set of rectangles.
I'm using Java and all of the rectangles are represented in integers (x,y,w,h). All rectangles are axis aligned with x/y axis.
Any suggestions?
You're going to potentially have a unique intersection between Rect1 and every rectangle in the RectSet union. So you are going to have do the intersection between Rect1 and each rectangle in the union separately. The intersecting area is the union of all intersecting sections between Rect1 and the rectangles in the union.
An optimization is to create a abounding rectangle for the union of rectangles (hopefully done as the union is created). If Rect1 doesn't intersect with this bounding rectangle, you can the skip doing any further intersections and the area in null.
An intersection of two rectangles is a rectangle itself (possibly degenerate, but those have zero area and can be ignored). Further, an intersection of unions is the same as a union of intersections (distributivity law). Therefore, you may intersect R1 with each of Rj and find the union of resulting rectangles.
To find the union, the easiest method is perhaps breaking the scene into vertical stripes, by drawing a vertical line through each vertex. Then within each stripe it's a well-known one-dimensional problem, solved by counting points in and out and removing those with count greater than one.
Go through and express your rectangles not as (x,y,w,h) but as (x1,y1,x2,y2), which is simply (x,y,x+w,y+h).
Then, loop over all Rj`s and "clip" the rectangles to the coordinates of Rect1:
Rj.x1 = max(Rj.x1, Rect1.x1)
Rj.y1 = max(Rj.y1, Rect1.y1)
Rj.x2 = min(Rj.x2, Rect1.x2)
Rj.y2 = min(Rj.y2, Rect1.y2)
Now, go through and remove any Rj's where Rj.x1>=Rj.x2 or Rj.y1>=Rj.y2 as in that case, the rectangles didn't intersect.
After, sum up all the areas of the remaining rectangles (simply (Rj.x2-Rj.x1) * (Rj.y2-Rj.y1)).
At this point, you will have double-counted any area where any of the clipped Rj`s overlap.
So, you then need to go through and loop over all Ri's and all Rj's where j>i and, clip the two with each other, but this time, if there is an intersection (same test as above), you need to subtract the area of the intersection from the value you have so far to remove the double-counting.
Unfortunately, this will double-remove any areas of a triple-overlap. So, you will then need to find those areas and add them back in. And so on and so forth for quadruple-overlaps, quintuple-overlaps, etc.
Sounds like it'll get pretty messy...
Maybe the easiest is to just draw the Rj's to a canvas in red and then count the red pixels inside Rect1 at the end. (Of course, you don't have to use a real Canvas. You can write your own using a bit-array.) There might even be scenarios (like a small coordinate space with lot's of tiny rectangles), where this is faster than the analytical solution. But, of course this will only work if you have integer coordinates.
Both n.m's answer and PQuinn's answer suggest to distribute the intersection across the union, then find the area of the union. That's a good idea.
In java, I suggest creating a new set of non-degenerate intersections between R1 and your Rj's, based on the assumption that most intersections will be degenerate. Then use the algorithm at http://codercareer.blogspot.com/2011/12/no-27-area-of-rectangles.html to find the area of the set of intersections.

Calculate shape orientation in Java (Image analysis)

I have an image such as this:
and I need to calculate the orientation of it. In this case the shape is pointing towards the top left of the screen. Accuracy isn't hugely important as long as 3 or 4 calculations average out to within 5 degrees or so of the actual orientation (it will be moving slightly).
Can anyone point me towards an algorithm to do this? I don't mind if the orientation is returned as a double or as a vector.
If the image is always T-shaped, you can simply get the furthest pair of pixels, then find the furthest pair from either both of those (the edges of the T), find which is further from the other two, draw a line from that one to the middle point of those two.
You can further refine it by then finding the base of the T by comparing the middle line with the edges of the base, and adjusting the angle and offset until it is actually in the middle.
The definitive solution is impossible I guess, since requires image recognition. I would project the 2D image onto axis, i.e. obtain the width and height of the image and get direction vector from these values taking them as components.
First, a couple of assumptions:
The center and centroid are "close"
The descending bar of the T is longer than the cross-bar
First, determine the bounding rectangle of the image and find the points of the image that lie along this rectangle. For points that lie along the line and are a certain distance from one another (say 5 pixels to pick a value) you'll need to only take 1 point from that cluster. At the end of this you should have 3 points, i.e. a triangle. The shortest side of the triangle should be the cross-bar (from assumption 2), i.e. find the two points closest to each other. The line that is perpendicular to the line crossing those two points is then your orientation line, i.e. find the angle between it and the horizontal axis.
I would try morphological skeletonization to simplify the image, followed by some straightforward algorithm to determine the orientation of the longer leg of the skeleton.
The solution in the end was to use a Convex Hull Algorithm, which finds the minimum number of points needed to enclose a shape with a bound.

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