In the MNIST dataset, are the images on white or black background? I seem to have encounter both type of images by googling around. Does the background color has any effects on the performance of a neural network in a recognition task?


The home of the MNIST dataset is at http://yann.lecun.com/exdb/mnist/

The page says: "Pixel values are 0 to 255. 0 means background (white), 255 means foreground (black)."

What matters to a neural net are the pixel values 0 (background) and 255 (foreground), though you can assign different colors to these pixel values when plotting the images.

A neural net trained on images with 0 as background and 255 as foreground will not be able to recognize images with inverted colors. You'd have a train a neural net on both types of images if you want it to work on both.

  • $\begingroup$ strangely, I have obtained better results by using black as background. Im not sure what is going on.. $\endgroup$ – dnth Aug 12 '15 at 9:14
  • $\begingroup$ What pixel value have you assigned to black? 0 or 255? If 0 is black, then the neural net should work fine. $\endgroup$ – stmax Aug 12 '15 at 9:55
  • $\begingroup$ yep zero is black. $\endgroup$ – dnth Aug 12 '15 at 10:35
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    $\begingroup$ That's why the neural net works.. it doesn't know about colors, only about pixel values (0 - 255). As long as the background is 0 and the digits are 255 it will work, no matter what color you assign to foreground/background. $\endgroup$ – stmax Aug 12 '15 at 11:23
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    $\begingroup$ @JackSimpson yes, the network's architecture can stay the same. Just train it with your own data. $\endgroup$ – stmax Feb 21 '17 at 13:57

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