Tag Archives: F#

F# Image Processing – Get Background Color

I recently had the need to get the background color of an image. The algorithm used to perform this is simple:

Get the image and find the color that occurs at least 3/4 of the time more than the next most occurring color in the image.

Here are some examples of images and what we would expect as a result.


The background image color is white.


The background image color is red.


The background image color is white.

Now, without further ado, here is the F# code. It should be relatively easy to follow.


open System
open System.Text.RegularExpressions
open System.IO
open System.Windows.Forms
open System.Windows.Forms.DataVisualization.Charting
open System.Diagnostics

let main (args: string[]) = 

    let sw = new System.Diagnostics.Stopwatch()
    for i = 21 to 21 do
        let img = "C:\\Temp\\ImageSamples\\" + Convert.ToString(i) + ".jpg"
        // get the image
        let bitmap = new System.Drawing.Bitmap(img)
        // process image
        let background = AboutDev.ImageProcessing.GetBackgroundColor(bitmap)
        printfn "%A is: %i, %i, %i" i background.R background.G background.B

    printfn "Time elapsed: %A" sw.Elapsed



namespace AboutDev

    #nowarn "9"
    open System
    open Microsoft.FSharp.NativeInterop
    open Microsoft.FSharp.Collections
    open System.Drawing
    open System.Drawing.Imaging 
    open System.Collections.Generic

    module ImageProcessing = begin

        let GetBackgroundColor (image:Bitmap) =

            // Get a Color from RGB values
            let GetColor x  = Color.FromArgb(Convert.ToInt32(int16 (NativePtr.get x 0)) , Convert.ToInt32(int16 (NativePtr.get x 1)) , Convert.ToInt32(int16 (NativePtr.get x 2)))

            // Check for grayscale images
            let IsGrayscale (x:Color) = x.R < 128uy && x.G < 128uy && x.B < 128uy

            // Create a thumbnail only if the image is more that the allowable size of 300 * 300 pixels
            let ToThumbnailOrNot (b:Bitmap) = 
                let maxAllowedDimensions = 300

                // Create a thumbnail that is sized proportionately to the original
                let CreateThumbnail (b:Bitmap) = 
                    let maxPixels = 100.0

                    // compute the scaling factor of the original image to our max allowed pixels
                    let scaling = if(b.Width > b.Height) then maxPixels / Convert.ToDouble(b.Width)
                                  else maxPixels / Convert.ToDouble(b.Height)
                    // compute the size of the new image as a sequence
                    let size = (Convert.ToInt32(Convert.ToDouble(b.Width) * scaling), Convert.ToInt32(Convert.ToDouble(b.Height) * scaling))
                    // create the thumbnail
                    new System.Drawing.Bitmap(b.GetThumbnailImage(fst size, snd size, null, IntPtr.Zero))

                if b.Width > maxAllowedDimensions && b.Height > maxAllowedDimensions then CreateThumbnail b
                else b

            // Get a thumbnail of the image if it is big or use the original image
            let img =  ToThumbnailOrNot image

            // dispose the original image because a copy was made in the previous statement

            // The array that is going to contain argb values to then do counts on
            let items = List<int32>()

            // lockbits on image so that the image can be processed quicker using unsafe means
            let bd = img.LockBits(Rectangle(0,0,img.Width,img.Height),ImageLockMode.ReadWrite,PixelFormat.Format32bppArgb)

            // pointer to use to go through the image
            let mutable (p:nativeptr<byte>) = NativePtr.ofNativeInt (bd.Scan0)
            for i=0 to img.Height-1 do
                for j=0 to img.Width-1 do
                    // Get the color of the [x,y] pixel
                    let colo = (GetColor p).ToArgb()
                    // add the ARGB value to our list
                    // move to the next pixel on the row
                    p <- NativePtr.add p 4
                // The stride - the whole length (multiplied by four to account for the fact that we are looking at 4 byte pixels
                p <- NativePtr.add p (bd.Stride - bd.Width*4)

            // Unlock the image bytes

            // test code to see the image we worked on
            //img.Save("C:\\temp\\result.jpg",  System.Drawing.Imaging.ImageFormat.Jpeg)

            // dispose the image that we worked on

            //List.ofSeq items |> Seq.countBy id |> Seq.sortBy (fun x -> (~-)(snd x) ) |> Seq.take 10 |> Seq.iter (printfn "%A")

            // get the first two item that occur the most in the array as a sequence
            let res = List.ofSeq items |> Seq.countBy id |> Seq.sortBy (fun x -> (~-)(snd x) )

            // Check to see that we have at least 2 colors
            if ( (Seq.length res) < 2) then res |> Seq.head |> fst |> Color.FromArgb

                let zero = Seq.head res     // first item in the sequence
                let one = Seq.nth 1 res     // second item in the sequence

                // Get the most prominent color
                let background = fst zero |> Color.FromArgb
                let background2 = fst one |> Color.FromArgb

                // Make sure the image is not grayscale and
                // the background color occurs at least 3/4 as much as the next closest color

                if( (IsGrayscale background) || (((Convert.ToDouble (snd zero)) * 0.75) < (Convert.ToDouble (snd one)))) 
                    then //printfn "Cannot determine color"
                         //printfn "First color is: %A, %A, %A" background.R background.G background.B
                         //printfn "Second color is: %A, %A, %A" background2.R background2.G background2.B
                    //printfn "%A, %A, %A" background.R background.G background.B
                    // Return the color

    end // End Module
NOTE: The sample code above is just that, a sample. You will need to play with it to do your bidding.

To set this up this comparison, I had a sample size of 20 images. The original code without my algorithm optimizations took 31.62 seconds to run. The F# code took 0.78 seconds.

Original Code F# Code
image image

Optimizations I made over the original code:

1. Use of LockBits

2. Creating thumbnails of the original image to work on instead of the original image when that image is large.

During my testing, I also created an image that was 13,648 * 7,912 and it took [00:00:01.2340651] to process it in my F# code. I had to stop the original C# code running on that image after 10 min! When I implemented my algorithm in C#, I was able to get the speed of the 20 images to 7.88 seconds. Still faster in F#.



F# allowed me to play with the algorithm very easily and tweak away until I got it just right.

You have to love the power of a language that lets you focus on the algorithm rather than on the minutiae of the language.

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Presentation Slides – An introduction to F#

On Saturday 5th November 2011, I presented a talk on F# and Functional Programming at Desert Code Camp. It was my first time at DCC and I must admit I thoroughly enjoyed interacting with people who enjoy technology and learning new things like me.I got to meet some great attendees and speakers. Lets not forget the immense time and effort given by the volunteers and organizers of Desert Code Camp as well.

I think the best part of my speech was getting people excited about F# and hearing the wows and praises for F# and my presentation after. You guys rock!

Also, congratulations to the two F# book giveaway winners.

I wanted to post the presentation slides for anyone who wanted it. I have tried to add the sample code to the presentation slides as well. Feel free to contact me if you have any questions.

An Introduction to F# – Sushant Bhatia (.PPTX)
An Introduction to F# – Sushant Bhatia (.PDF)

Edit: The presentation is not looking nice in Google Docs. I will try and get a PDF of the entire presentation up tonight. It should also contain the notes that I put so that you can try out the code.

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