Always looking for some ways to learn the computer to ‘see’, I came accross two very interesting algorithms: ‘Real-time Contrast Preserving Decolorization’ by Cewu Lu, Li Xu and Jiaya Jia. And Potrace by Peter Selinger

Decolorization – the process to transform a color image to a grayscale one – is a basic tool in digital printing, stylized black-and-white photography, and in many single channel image processing applications. RTCPD is aiming at maximally preserving the original color contrast alleviate a strict order constraint for color mapping based on human vision system.

The second algorithm Potrace(TM) is a tool for tracing a bitmap, which means, transforming a bitmap into a smooth, scalable image.

Playing around with both algorithms, I came up with the idea to use them for a project I had in mind for some time: Sketching pictures on my wall using a Pico projector.

First I had to implement both algorithms in Xojo. The result of RTCPR can be found in the attached source code in the RTCPRGB2Gray() method:

Private Sub RTCPRGB2Gray(pic as Picture) dim imcols as Integer = pic.Width dim imrows as Integer = pic.Height dim sRGB as RGBSurface = pic.RGBSurface dim Mat(-1,-1) as ABDoubleVector redim Mat(imrows-1,imcols-1) dim c as Color for y as Integer = 0 to imrows - 1 for x as Integer = 0 to imcols - 1 c = sRGB.Pixel(x,y) mat(y,x) = new ABDoubleVector(c.Blue, c.Green, c.Red) ' switch to BRG next next dim s as Double = 64.0 / sqrt(imcols*imrows) dim cols as Integer = (s * imcols) + 0.5 dim rows as Integer = (s * imrows) + 0.5 dim sigma as Double = 0.05 dim W() as ABDoubleVector = wei() dim P() as ABDoubleVector dim det() as Double dim pos0() as ABDoublePoint dim pos1() as ABDoublePoint for i as Integer = 0 to cols - 1 for j as Integer = 0 to rows - 1 dim x as Integer = (i+0.5) * imcols/cols dim y as Integer = (j+0.5) * imrows/rows pos0.Append new ABDoublePoint(x,y) pos1.Append new ABDoublePoint(x,y) next next pos1.Shuffle for i as Integer = 0 to pos0.Ubound dim c0 as ABDoubleVector = mat(pos0(i).y, pos0(i).x) dim c1 as ABDoubleVector = mat(pos1(i).y, pos1(i).x) add c0,c1, P, det next cols = cols / 2 rows = rows / 2 for i as Integer = 0 to cols - 2 for j as integer = 0 to rows - 1 dim x0 as integer = (i + 0.5) * imcols / cols dim x1 as integer = (i + 1.5) * imcols / cols dim y as integer = (j + 0.5) * imrows / rows dim c0 as ABDoubleVector = mat(y, x0) dim c1 as ABDoubleVector = mat(y, x1) add(c0, c1, P, det) next next for i as integer = 0 to cols - 1 for j as Integer = 0 to rows - 2 dim x as integer = (i + 0.5) * imcols / cols dim y0 as integer = (j + 0.5) * imrows / rows dim y1 as integer = (j + 1.5) * imrows / rows dim c0 as ABDoubleVector = mat(y0, x) dim c1 as ABDoubleVector = mat(y1, x) add(c0, c1, P, det) next next dim maxES as Double = -99999999999 dim bw as Integer for i as integer = 0 to w.Ubound dim es as Double for j as integer = 0 to p.Ubound dim l as Double = P(j).x * W(i).x + P(j).y * W(i).y + P(j).z * W(i).z dim detM as Double = det(j) dim a as double = (L + detM) / sigma dim b as double = (L - detM) / sigma es = es + log(exp(-a * a) + exp(-b * b)) next es = es / (p.Ubound+1) if eS > maxEs then maxEs = Es bw = i end if next dim result(-1,-1) as Double redim result(imrows-1,imcols-1) for y as Integer = 0 to imrows - 1 for x as Integer = 0 to imcols - 1 result(y,x) = mat(y,x).z*W(bw).x + mat(y,x).y*w(bw).y+0 result(y,x) = mat(y,x).x*W(bw).z + result(y,x)*1+0 sRGB.Pixel(x,y) = rgb(result(y,x),result(y,x),result(y,x)) next next bw = 0 End Sub

Potrace is a complete framework to trace an image and converting it to Xojo did take some time. While writing it, I also made some changes to it to optimize the result. One of it was doing my own thresholding using the surrounding pixels to smoothen the edge detection.

Snippet:

dim v, v1, v2, v3, v4, v5, v6, v7, v8 as Integer dim ex,ey, weight, weighttotal, total as Double 'SISThreshold2 alain for y = 1 to H - 2 for x = 1 to W - 2 v = sDebugPicRGB.Pixel(x, y).red v1 = sDebugPicRGB.Pixel(x+1, y).red v2 = sDebugPicRGB.Pixel(x-1, y).red v3 = sDebugPicRGB.Pixel(x, y+1).red v4 = sDebugPicRGB.Pixel(x, y-1).red v5 = sDebugPicRGB.Pixel(x+1, y-1).red v6 = sDebugPicRGB.Pixel(x-1, y-1).red v7 = sDebugPicRGB.Pixel(x+1, y+1).red v8 = sDebugPicRGB.Pixel(x-1, y+1).red ex = (v1+v2+v5+v6)/4 ey = (v3+v4+v7+v8)/4 if ex > ey then weight = ex else weight = ey end if weighttotal = weighttotal + weight total = total + weight * (v) next next dim Threshold as Integer = 128 if weighttotal <> 0 then Threshold = total/weighttotal end if dim ret as Boolean = (sDebugPicRGB.Pixel(0, 0).Red >= Threshold) for y = 0 to H for x = 0 to W c = sDebugPicRGB.Pixel(x, y) if c.red >= Threshold then Matrix(x+1, y + 1) =true else Matrix(x+1, y + 1) = false end if next next for x = 0 to MatrixW Matrix(x,0) = true Matrix(x, MatrixH) = true next for y = 0 to MatrixH Matrix(0,y) = true Matrix(MatrixW, y) = true next

This gave me all the tools to start tracing an image. But for my project I wanted to have a sort of ‘sketchy’ feeling. For this I needed a couple of things because I wanted the drawing and painting to be done gradually. I had to build it with delays, repetition, randomization and color fading. I wanted to start from a picture and create something like this:

DrawImage() does all that. It first draws the beziers with some little random mistakes in grey. A gradual painting is then used to fill in the polygons. Finaly it repeats the process with the correct lines in white.

You may notice that a lot of code is redundant, but this is intended because I needed to have enough delays to mimic a more natural feeling.

Here is a demo video showing the result of this project on my wall. It takes about ten seconds before it starts drawing as I had to grab my camera :-). Five different images are drawn.

The project with full source code can be downloaded here

Greetz!

Alwaysbusy

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