Data structure designed specifically for a drawing tool application

Currently, I am in the process of developing a unique sketching application using the HTML5 Canvas element. Despite my progress, there is one particular challenge that has stumped me.

The main concept of the application involves allowing users to manipulate existing stroke data (points) with complete freedom. This includes the ability to push points around as if using a magnet tool and changing their characteristics such as color.

It's worth noting that the current brush engine has the capability to create shading by considering existing stroke data. However, this method is somewhat rudimentary as it simply checks each point in the stroke against a certain distance rule.

The real issue lies in finding an efficient way to access all points within a given canvas coordinate and radius for manipulation. While other features are important, such as minimizing space usage, the primary focus should be on performing queries effectively. I don't mind implementing additional processing between strokes when the user is not actively painting.

If you have any advice or suggestions, they would be greatly appreciated. :)

Answer №1

If you're looking for a common solution to handling random sets of points in 2D, consider utilizing a quadtree space partitioning technique. You can find more information about quadtree on this Wikipedia link: http://en.wikipedia.org/wiki/Quadtree

Answer №2

If you're interested in exploring the concept of spatial indexing, Johan recommended looking into quadtree which is a good suggestion. Other data structures worth considering include:

Answer №3

My preference would be to utilize a basic matrix structure like int pixels[][]. This allows for each pixel at coordinates x,y to store its color value.

I fail to see any significant benefit in implementing more intricate data structures. A matrix is not only efficient but also user-friendly. In terms of operations, such as obtaining points based on given coordinates and radius, one can easily calculate the math using matrix indices and fetch the corresponding pixels swiftly. It's incredibly quick.

Answer №4

In my approach, I essentially encapsulate an array within an object with specialized functions for manipulating the pixel data or extracting samples from it. This methodology was utilized in a previous project related to weather erosion, where a Gaussian function was employed for both sampling and redistributing data based on a circular weighting principle.

To enable undo functionality or interactions between brush strokes, one would need a mapping of pixels corresponding to each individual 'brushstroke'. This concept could be represented by a separate object, with all brushstrokes referencing a central matrix containing information about the points they affect - potentially including weight values indicating the contribution of color to each point.

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