/// <summary> <p>This is called when a horizontal scan finds a possible alignment pattern. It will
/// cross check with a vertical scan, and if successful, will see if this pattern had been
/// found on a previous horizontal scan. If so, we consider it confirmed and conclude we have
/// found the alignment pattern.</p>
///
/// </summary>
/// <param name="stateCount">reading state module counts from horizontal scan
/// </param>
/// <param name="i">row where alignment pattern may be found
/// </param>
/// <param name="j">end of possible alignment pattern in row
/// </param>
/// <returns> {@link AlignmentPattern} if we have found the same pattern twice, or null if not
/// </returns>
private AlignmentPattern handlePossibleCenter(int[] stateCount, int i, int j)
{
int stateCountTotal = stateCount[0] + stateCount[1] + stateCount[2];
float?centerJ = centerFromEnd(stateCount, j);
if (centerJ == null)
{
return(null);
}
float?centerI = crossCheckVertical(i, (int)centerJ, 2 * stateCount[1], stateCountTotal);
if (centerI != null)
{
float estimatedModuleSize = (stateCount[0] + stateCount[1] + stateCount[2]) / 3.0f;
foreach (var center in possibleCenters)
{
// Look for about the same center and module size:
if (center.aboutEquals(estimatedModuleSize, centerI.Value, centerJ.Value))
{
return(center.combineEstimate(centerI.Value, centerJ.Value, estimatedModuleSize));
}
}
// Hadn't found this before; save it
var point = new AlignmentPattern(centerJ.Value, centerI.Value, estimatedModuleSize);
possibleCenters.Add(point);
if (resultPointCallback != null)
{
resultPointCallback(point);
}
}
return(null);
}
/// <summary> <p>This method attempts to find the bottom-right alignment pattern in the image. It is a bit messy since
/// it's pretty performance-critical and so is written to be fast foremost.</p>
///
/// </summary>
/// <returns> {@link AlignmentPattern} if found
/// </returns>
internal AlignmentPattern find()
{
int startX = this.startX;
int height = this.height;
int maxJ = startX + width;
int middleI = startY + (height >> 1);
// We are looking for black/white/black modules in 1:1:1 ratio;
// this tracks the number of black/white/black modules seen so far
int[] stateCount = new int[3];
for (int iGen = 0; iGen < height; iGen++)
{
// Search from middle outwards
int i = middleI + ((iGen & 0x01) == 0 ? ((iGen + 1) >> 1) : -((iGen + 1) >> 1));
stateCount[0] = 0;
stateCount[1] = 0;
stateCount[2] = 0;
int j = startX;
// Burn off leading white pixels before anything else; if we start in the middle of
// a white run, it doesn't make sense to count its length, since we don't know if the
// white run continued to the left of the start point
while (j < maxJ && !image[j, i])
{
j++;
}
int currentState = 0;
while (j < maxJ)
{
if (image[j, i])
{
// Black pixel
if (currentState == 1)
{
// Counting black pixels
stateCount[currentState]++;
}
else
{
// Counting white pixels
if (currentState == 2)
{
// A winner?
if (foundPatternCross(stateCount))
{
// Yes
AlignmentPattern confirmed = handlePossibleCenter(stateCount, i, j);
if (confirmed != null)
{
return(confirmed);
}
}
stateCount[0] = stateCount[2];
stateCount[1] = 1;
stateCount[2] = 0;
currentState = 1;
}
else
{
stateCount[++currentState]++;
}
}
}
else
{
// White pixel
if (currentState == 1)
{
// Counting black pixels
currentState++;
}
stateCount[currentState]++;
}
j++;
}
if (foundPatternCross(stateCount))
{
AlignmentPattern confirmed = handlePossibleCenter(stateCount, i, maxJ);
if (confirmed != null)
{
return(confirmed);
}
}
}
// Hmm, nothing we saw was observed and confirmed twice. If we had
// any guess at all, return it.
if (possibleCenters.Count != 0)
{
return(possibleCenters[0]);
}
return(null);
}
/// <summary>
/// Processes the finder pattern info.
/// </summary>
/// <param name="info">The info.</param>
/// <returns></returns>
protected internal virtual DetectorResult processFinderPatternInfo(FinderPatternInfo info)
{
FinderPattern topLeft = info.TopLeft;
FinderPattern topRight = info.TopRight;
FinderPattern bottomLeft = info.BottomLeft;
float moduleSize = calculateModuleSize(topLeft, topRight, bottomLeft);
if (moduleSize < 1.0f)
{
return(null);
}
int dimension;
if (!computeDimension(topLeft, topRight, bottomLeft, moduleSize, out dimension))
{
return(null);
}
Internal.Version provisionalVersion = Internal.Version.getProvisionalVersionForDimension(dimension);
if (provisionalVersion == null)
{
return(null);
}
int modulesBetweenFPCenters = provisionalVersion.DimensionForVersion - 7;
AlignmentPattern alignmentPattern = null;
// Anything above version 1 has an alignment pattern
if (provisionalVersion.AlignmentPatternCenters.Length > 0)
{
// Guess where a "bottom right" finder pattern would have been
float bottomRightX = topRight.X - topLeft.X + bottomLeft.X;
float bottomRightY = topRight.Y - topLeft.Y + bottomLeft.Y;
// Estimate that alignment pattern is closer by 3 modules
// from "bottom right" to known top left location
//UPGRADE_WARNING: Data types in Visual C# might be different. Verify the accuracy of narrowing conversions. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1042'"
float correctionToTopLeft = 1.0f - 3.0f / (float)modulesBetweenFPCenters;
//UPGRADE_WARNING: Data types in Visual C# might be different. Verify the accuracy of narrowing conversions. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1042'"
int estAlignmentX = (int)(topLeft.X + correctionToTopLeft * (bottomRightX - topLeft.X));
//UPGRADE_WARNING: Data types in Visual C# might be different. Verify the accuracy of narrowing conversions. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1042'"
int estAlignmentY = (int)(topLeft.Y + correctionToTopLeft * (bottomRightY - topLeft.Y));
// Kind of arbitrary -- expand search radius before giving up
for (int i = 4; i <= 16; i <<= 1)
{
alignmentPattern = findAlignmentInRegion(moduleSize, estAlignmentX, estAlignmentY, (float)i);
if (alignmentPattern == null)
{
continue;
}
break;
}
// If we didn't find alignment pattern... well try anyway without it
}
PerspectiveTransform transform = createTransform(topLeft, topRight, bottomLeft, alignmentPattern, dimension);
BitMatrix bits = sampleGrid(image, transform, dimension);
if (bits == null)
{
return(null);
}
ResultPoint[] points;
if (alignmentPattern == null)
{
points = new ResultPoint[] { bottomLeft, topLeft, topRight };
}
else
{
points = new ResultPoint[] { bottomLeft, topLeft, topRight, alignmentPattern };
}
return(new DetectorResult(bits, points));
}