OCR’ing a power meter

The following shows the output of the IP camera which is photographing the power meter (what the photo doesn’t show is a large high powered light just above the power meter, to keep the output nice and clear):

We then threshold the image so that the numbers are clearly recognizable:

Seven points where then taken from the LCD segments and mapped to a list, we are then able to compare the list to known values for different digits:

We moved the points across the image to detect each of the digits on the power meter.

The following shows the output from 1 hours worth of samples from a blade server, taken each minute:

The following is the Mathematica sourcecode:

datav = {}

For][[1]];

 powermeter = 
  Binarize[GaussianFilter[Binarize[powermeter, 0.27], 1], 0.20];

 output = 0;
 For[z = 0, z <= 3, z = z + 1,
  x = z*20;
  seg = {ImageValue[powermeter, {73 - x, 225}], 
    ImageValue[powermeter, {79 - x, 231}], 
    ImageValue[powermeter, {84 - x, 220}], 
    ImageValue[powermeter, {78 - x, 216}], 
    ImageValue[powermeter, {72 - x, 209}], 
    ImageValue[powermeter, {78 - x, 201}], 
    ImageValue[powermeter, {84 - x, 206}]};
  
  digit = -1;
  If[seg == {0, 0, 0, 1, 0, 0, 0}, digit = 0] ;                                         
  If[seg == {1, 1, 0, 1, 1, 1, 0}, digit = 1];
  If[seg == {1, 0, 0, 0, 0, 0, 1}, digit = 2];
  If[seg == {1, 0, 0, 0, 1, 0, 0}, digit = 3];
  If[seg == {0, 1, 0, 0, 1, 1, 0}, digit = 4];
  If[seg == {0, 0, 1, 0, 1, 0, 0}, digit = 5]; 
  If[seg == {0, 0, 1, 0, 0, 0, 0}, digit = 6];
  If[seg == {1, 0, 0, 1, 1, 1, 0}, digit = 7];
  If[seg == {0, 0, 0, 0, 0, 0, 0}, digit = 8];
  If[seg == {0, 0, 0, 0, 1, 0, 0}, digit = 9];  
  output += digit*(10^(z - 1));

  ];
 
 If[output <= 300, output *= 10];
 datav  = Append[datav, output];
 Pause[60];
 ]

ListLinePlot[datav, {Filling -> Axis, AxesOrigin -> {0, 0}}]

As it’s hard to recognize the decimal point in the image, I use knowledge of the fact my blade server is unlikely to be running at <=300W so it should in-fact be running at 3000W. This is accounted for in this line: If[output <= 300, output *= 10]; I tried an alternative approach whereby I attempted correlation between a digit in the photo and each of the respective digits 0-9 in a training file, I think because of the noise in the image and various jpeg artifacts, the comparison of the different digits was to poor.