So there us a billion and one articles about cropping an image inside a shape. But how do I crop a shape inside a shape?
Lets say I have a star shape inside a rectangular shape and I only want to draw the part of the star that's inside the rectangular.
In PowerPoint - how do I crop a shape inside another shape so nothing from the first shape is drawn outside the second shape?
Related
I'm trying to write a small drawing app where I want to be able to draw shapes by hand and the app will identify the kind of shape and redraw it using vector graphics.
Supposing that I have a list of 2D points that represent the following image:
What algorithms should I use in order to:
Determine that the shape is a square and not another shape or curve/arc;
Determine the edges of the square
Image files are rectangular, yet in a 3D environment, a rectangle will appear as an irregular quadrilateral most of the time. Consider the following image (credit to this blog):
Given that:
you already know the four vertices of the green face
you have access to the image file as a 2D array of color values
you are drawing to a screen that is a 2D array of pixels
What is the algorithm that OpenGL uses for drawing the image onto the green face?
The algorithm is basically (if we ignore stuff like shaders for now):
break down the quadrilateral into two triangles
for each triangle, compute the projection onto the image plane
for each screen pixel covered by the projection of the triangle:
compute the texture coordinates by interpolation from the vertices for the position to which the pixel location corresponds on the triangle.
look up the texture image at the location that corresponds to the texture coordinates. Typically, some form of filtering is applied here.
you have found the color for your pixel
I have a set of rectangle tiles, each of them with different shapes on them. One tile could for example contain the texture of a circle, another a rectangle, or maybe even a polygon.
These shapes do not fill up the whole tile, instead they are somewhere on the texture. One tile could for example just contain a small rectangle in the top-right corner. The other parts of the tiles are empty or transparent, i.e. these other pixels have an alpha value of 0.
Now I need to calcuate the "center of gravity" (CoG) within each tile. I know that is not be the best term to describe it, but I don't know of any better. With CoG in this context I mean the spot on the tile that is the center point of the shapes, i.e. those parts of the tiles that are not transparent.
For example, if the tile has one small rectangle in the top-right corner, then the CoG as I mean it would be in the center of the rectangle. In this case thus that CoG would not be in the center of the tile, but also somewhere in the top-right corner.
Important is that fact that the color of the shapes do not count. I am solely interested in the transparent vs. non-transparent pixels/areas on the tile.
Is there any "best practice" to calculate what I am looking for?
Here is the original image, the green colour is the background, and blue is the shape.
If my eye go closer to the shape, the blue square will be bigger like this:
If my eye go left, the shape will work like this:
I already know my eyes movement position, but how can I calculate what will the shape change? Any recommends? Thanks.
You need know the camera matrix http://en.wikipedia.org/wiki/Camera_matrix it will define the way which 3D coord will be projected to your sreen coordinates. If you know orientation of your camera, then you know 3d coords of object points relative to camera. Applying camera matrix transform to these 3d coords will give you 2d projections in you screen coordinates.
I am writing a program in Matlab to detect a circle.
I've already managed to detect shapes such as the square, rectangle and the triangle, basically by searching for corners, and determining what shape it is based on the distance between them. The images are black and white, with black being the background and white the shape, so for me to find the corners I just have to search each pixel in the image until I find a white pixel.
However I just can't figure out how I can identify the circle.
Here it the an example of how a circle input would look like:
It is difficult to say what the best method is without more information: for example, whether more than one circle may be present, whether it is always centred in the image, and how resilient the algorithm needs to be to distortions. Also whether you need to determine the location and dimensions of the shape or simply a 'yes'/'no' output.
However a really simple approach, assuming only one circle is present, is as follows:
Scan the image from top to bottom until you find the first white pixel at (x1,y1)
Scan the image from bottom to top until you find the last white pixel at (x2,y2)
Derive the diameter of the suspected circle as y2 - y1
Derive the centre of the suspected circle as ((x1+x2)/2, y1+(y2-y1)/2)
Now you are able to score each pixel in the image as to whether it matches this hypothetical circle or not. For example, if a pixel is inside the suspected circle, score 0 if it is white and 1 if it black, and vice-versa if it is outside the suspected circle.
Sum the pixel scores. If the result is zero then the image contains a perfect circle. A higher score indicates an increasing level of distortion.
I think you may read about this two topics:
Theoretical:
Binary images
Hough transform
Matlab:
Circle Detection via Standard Hough Transform
Hough native in matlab
Binary images