So i need to create a border mesh from 2 different pointsets that have their own length. The "mesh" needs to be a list of polygons that are sorted clockwise, the polygons can contain any number of points.
image of problem
I used to do this by looping through the points in the outer set, and for each point I would connect it to the closest point of the inner set. After that I would make faces with 4 points out of the lines I made. This worked perfectly.
But now we run into the problem that the outer point set no longer has the same length as the inner set. So our current approach will no longer work.
if someone could help me in the right direction or with an example on how to achieve this that would be greatly appreciated
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I'm making a game, where levels are grid based.
At first, I have rectangle MxM cells. Then within this rectangle I have to put rooms. Room is another rectangle which is AxB cells, where 2 <= A, B <= 4. Besides, It's necessary to put N rooms in each row and N ones in each column. They should fill all the space, there can't be empty space between them. In other words, I have to feel rectangle with other rectangles the way that there will no be empty space between them and they will form a grid with N rows and N columns.
What I did:
I store information about rooms in form of their left-top corner, calculate it and then put rooms based on their and neighbor's corners. To do that:
Divide grid on rooms 3x3
In each of 3x3 rooms define area which is obligatory floor (2x2 square, let's call it red area)
In loop for each room count it's neighbor x and y corner position the way that it doesn't cross none of the obligatory floor ares. For that:
a. Get red area of current room and it's neighbors. Set corner somewhere between them, making sure the dimensions of the room are within range above.
b. Resolve collisions, when it's not possible to set random corner. For instance, if x position of room above isn't equal to our room, then we can't put horizontal wall between to rooms righter them in random y position, because in that case these rooms will overlap each other.
Some other stuff with converting information about corners to rooms themselves
So, what's the problem? My code with a lot of if-statements and crutches became so unreadable and huge that it almost impossible to test and find bugs. Approach I used seems to work but it's impossible to control the way it's working or not working.
Another issue is that I want to have more control on how it looks like. Grid must be interesting, which means that neighbor rooms are preferably not of the same size. There's an example (grid) of such a grid (with red areas that are gray there), which is not bad.
Is there some alternative to solve this? In other questions I saw a lot of similar solutions, but all of them doesn't assume that there's fixed amount of rows and columns.
Recommend me some articles I haven't managed to find, probably, literature devoted to this topic, or point the direction where to move and find a working solution.
A traditional method of generating grids containing rooms is to use Binary-Space-Partition trees.
One thing about that method is that it often produces grids that are less densely populated than your example. You might be able to modify some BSP example code and make the map more dense though.
Another possible approach would be to generate the rectangles first, (perhaps with a border along two edges for the gap) then try to pack them using a rectangle packing algorithm. This previous answer has several potential packing algorithms.
So, I'm using a boolean operator to get the intersection of a bunch of pieces and a wall. Most pieces work fine but occasionally the intersection isn't perfect and you get these vertices that aren't connected to the rest of the mesh and this results in the mesh collider being incorrect, as seen in this picture.
My question is whether there is a way to detect these 'island' or 'lone' vertices.
I can provide additional images, code, or such if needed.
Thanks for any help! Ps. first question here so please be patient with me :)
In the end, I kind of solved it by finding all connected vertices starting from a single vertex.
I started by picking the first triangle and adding it's vertices to a list of connected vertices. Then I go through the list of triangles comparing the position of their vertices to the list of connected vertices. If the triangle has a vertex with a position corresponding to a position in the list of connected vertices I add the entire triangle to the list. That's one iteration and I repeat this until all connected triangles are already in the list. If the connected triangle list is more than half of all triangles then I remove all other triangles, otherwise, I remove the current list of connected triangles. After that, I clear the vertices that aren't in a triangle like Leo Bartkus suggested.
It's extremely slow and it assumes there are only 2 separate islands or that you started on the biggest island, but it worked most of the time and was more for learning purposes anyways.
Thank's for the help!
I have been attempting to fill in a binary image in Matlab so that I am left with the entirety of this oval-like image like this.
However, I have been running into an issue in actually being able to define the red region. I have tried the following:
Using the bwconvhull function to fill the shape accurately, but then I do not know how to get rid of the inner shape to isolate just the red region.
I have also attempted to trace the boundary of the binary region but to no avail. I am not entirely sure what to do after tracing the boundary. I have attempted to trace just the inner boundary, but the bwtraceboundary function simply follows the entirety of the borders (on the inside and outside of the skull).
Are there any similar functions to bwconvhull where I am able to expand a region from the center outward? My major difficulties have been in isolating either (a) the inner boundary of the skull or (b) the inner "black" region where the brain should be. My coding attempts can be found below:
Issue (a) - Tracing boundaries
hole=imread('Copy CT.jpg');
BW=im2bw(hole,.9);
dim=size(BW);
col=round(dim(2)/2);
row=min(find(BW(:,col)));
boundary = bwtraceboundary(BW,[row,col],'S');
x=boundary(:,2);
y=boundary(:,1);
Issue (b) - Isolating only the center
hole=imread('Copy CT.jpg');
BW=im2bw(hole,.9);
CH=bwconvhull(BW);
KH=CH-BW;
KH2=bwareaopen(KH,200);
Are there any particular functions that would be worth trying, or would there be another way to isolate the center of the circle so I can only highlight the red region? Any insight would be greatly appreciated!
I would approach this with these steps:
apply an edge detection filter so you end up with two ellipse-ish shaped parts: an inner and outer ellipse.
apply an algorithmic ellipse-fit to the inner ellipse. There are some good examples out there, but I don't have one on me.
subtract the bwconvhull boundary with the inner ellipse.
subtract all parts of your new oval that overlap with the white portions of the original image.
I am sorry I don't have actual code to back up this approach, but this will get you pretty close. You may need more steps to clean up the final result.
I got an experimental data set that looks more or less like this.
I need to determine how big the hysteresis loop is, aka if I look at two points with the same capacity (Y axis), whats the maximum distance between said points (X axis).
The issue is, data points arent located on the same Y value, aka I cant just find max X and min X for every Y and subtract them - that'd be too easy :^)
I figured I can use convex hull (convhull) to calculate the outer envelope of the set, but then I realised, it will only work for the convex part, not the concaved part, but I guess I can divide my data set into smaller subsets and find a sum of them... or something.
And then, assuming I have the data set thats only the outer outline of the data set, I need to calculate distances between left and right border (as shown here), but then again, thats just data set of X and Y, and Id need to find the point where green line crosses outer rim
So here are the questions:
Is there a matlab procedure that calculates the outer outline of data set, that works with the concaved part - kinda like convhull, but better?
Assuming I have the outline data set, is there an easy way to calculate secant line of data set, like shown on second picture??
Thanks for any advice, hope I made what I have in mind clear enough - english isnt my first language
Benji
EDIT 1: Or perhaps there is an easier (?) way to determine, which points form biggest outline? Like... group points into (duh) groups, lets say, those near 20%, 30%, 40%... and then pick two randomly (or brute force pick all possible pairs), one for top boundary, other for bot boundary, and then calculate area of polygon formed this way? Then, select set of points resulting in polygon with biggest area?
EDIT 2: Ooor I could group them like I thought I would before, and then work on only two groups at a time. Find convex hull for two groups, then for two next groups, and when Im done with all the groups, Id only need to find points common to all the group, and find a global hull :D Yeah, that might work :D
I have some data points which I have devided into them into some clusters with some clustering algorithms as the picture below:(it might takes some time for the image to appear)
alt text http://www.freeimagehosting.net/uploads/05a807bc42.png
Each color represents different cluster. I have to draw polygons around each cluster. I use convhull for this reason. But as you can see the polygon for the red cluster is very big and covers a lot of areas, which is not the one I am looking for. I need to draw lines(ploygons) exactly around my data sets. For example in the picture above I want a polygon that is drawn exactly the same(and around) as the red cluster with the 3 branches. In other words, in this case I need a polygon with 3 branches to cover my red clusters not that big polygon that covers the whole area. Can anyone help me with this?
Please Note that the solution should be general, because the clusters will change in each run of the algorithm, so it needs to be in a way that is general.
I am not sure this is a fully specified question. I see this variants on this question come up quite often.
Why this can not really be answered here: Imagine six points, three in an equilateral triangle with another three in an equilateral triangle inside it in the same orientation.
What is the correct hull around this? Is it just the convex hull? Is it the inner triangle with three line spurs coming out from it? Does it matter what the relative sizes of the triangles are? Should you have to specify that parameter then?
If your clusters are very compact, you could try the following:
Create a grid, say with a spacing of 0.1.
Set every pixel in the grid to 1 if there's at least one data point covering it, set the pixel to 0 if there is no data point covering the pixel.
You may need to run imclose on your mask in order to fill little holes inside that have not been colored due to sheer bad luck.
Extract the border pixels using, e.g. bwperim. This is the outline of the polygon you're looking for.