It's a kind of lithophane; with the provided Matlab files and ImageJ you can create a Pseudo-3D model / "lithophane" of an image based on its intensity/gray values. (In my opinion this is not exactly a lithophane, because you don't need to lit it with a light source.) Import your desired RGB-image to Matlab (drag and drop). For example: "image2D.jpg". For example: clusteredImage = clusterImage(image2D,16); To create the pseudo-3D model use the function "calcPseudo3dModel". This guy takes two parameter: the cluster result of step 2 and the number of desired depth layers (this value determines the heights of your pseudo-3D model. For example: pseudo3dModel =calcPseudo3dModel(clusteredImage ,32) With the function 'savePseudo3dModel' you save the created pseudo-3D model as a sequence of images. This function takes three parameters; a pseudo- 3D model, a file name and a flag. If the flag is set to 1 the 3D model or better the cluster result will be inverted and if the flag is set to 0 it won't be inverted. For example: savePseudo3dModel(pseudo3dModel, 'semih',0); Import the image sequence into ImageJ and open the 3D Viewer. Select 'Display as: Surface', 'Color: White' and 'Resampling factor: 1'. Export the model: File->Export surface as-> STL(binary)