I have a problem where I need to define a polygon with the minimum number of vertices that intersects or contains every pixel in an image that is not transparent (Let N be the number of pixels in the image). My only assumptions are that the image cannot contain transparent pixels within its boundary (holes), and that at least two pixels are non-transparent. As an example, lets say I have the following image:
My idea for an algorithm is thus:
1) Determine the edge pixels.
This is done in O(N) time by iterating through each pixel, and determining whether any neighbors (out of the four pixels left, above, right, and below it) are empty. Store the pixel and which neighbors were non-transparent, keyed by linear index into the array of pixels. Let there be P edge pixels, shown in orange below.
2) Get an adjacency list of the edge pixels.
This is done in O(P) time by selecting one of the edge pixels, and chosing a direction based on empty neighbors. For example, if a pixel has a bottom and right neighbor, then the next pixel will be either one in the upper-right corner, or the pixel immediately to the right. Select the next edge pixel from the dictionary of remaining edge pixels. Append that pixel to the list until the algorithm returns to the starting pixel. There are 27 edge pixels in the example image below (some are an edge pixel more than once).
3) Draw a maze that all edges must lie between.
This is done in O(P) time by iterating through the adjacency list, and adding an edge to all edges on those pixels without a neighbor. In addition, an edge is added to the interior of the shape based on the direction to the next edge pixel. If the pixel represents a peninsula with single pixel width, the inner edge is added to the middle of the edge instead of the pixel vertex. The interior of the maze is shown in red. Note that the maze boundary is a super-set of all the edge pixels found in step 2.
4) Find a polygon with almost minimal edges that does not touch the border of the maze.
This is the part I need help with. Does anyone have a suggestion of how you would go from step #3 to a solution such as the following?
Here the inverted source code in C++ (there may be some hole comments left):
map[][]
conditions inverted to search polygons instead of holes_lin
coordinates arefloat
now so o need for 4x multisamplingmap[][]
and your imageI have no background in image processing, but I came across the Ramer–Douglas–Peucker algorithm yesterday and I think it might be helpful.
From my quick scan of the Wikipedia article, it reduces the number of point in a curve, so I would run this algorithm on each line where the points of the line are the end points you have and also set as points the borders of squares that the line crosses.
I marked out in this image two lines you could run the algorithm on and I think it would work.
How to find each line and when to stop - not 100% sure, but I hope this was useful.