Build triangulations from image vectorizations

Instead of building constraints by exhaustively write set of coordinates, you can generate them by vectorization of black and white images.

How to create an object from image

You can use the following static to create new DDLSObject instances from images:

DDLSBitmapObjectFactory.buildFromBmpData(bmpData:BitmapData):DDLSObject

example:

// build a rectangle mesh
var mesh:DDLSMesh = DDLSRectMeshFactory.buildRectangle(600, 400);

// we draw a black circle on Shape
var shape:Shape = new Shape();
shape.graphics.beginFill(0x000000);
shape.graphics.drawCircle(50, 50, 48);
shape.graphics.endFill();

// make a white BitmapData and then transfer the Shape on it
var bitmapData:BitmapData = new BitmapData(100, 100, false, 0xFFFFFF);
bitmapData.draw(shape);

// finally build the DDLSObject instance from the BitmapData
var object:DDLSObject = DDLSBitmapObjectFactory.buildFromBmpData(bitmapData);

// insert, tranform and update opbject
mesh.insertObject(object);
object.x = 100;
object.y = 100;
mesh.updateObjects();

// display
var view:DDLSSimpleView = new DDLSSimpleView();
addChild(view.surface);
view.drawMesh(mesh);

result:

Because the underlying implementation is inspired by the Potrace algorithm, you should remember to use images made from 2 colors only: black (0x000000) and white (0xFFFFFF). If your image contains other colors, a threshold will be applied and any color different from white will be considered as black.

As a recommendation, you should be careful about the size of the images you use. High resolution images can lead to a long time to process.

black and white 400x400 image example:

result after triangulation:

Next : Solve pathfinding requests