/*\r
- * Copyright 2007 Google Inc.\r
+ * Copyright 2007 ZXing authors\r
*\r
* Licensed under the Apache License, Version 2.0 (the "License");\r
* you may not use this file except in compliance with the License.\r
\r
package com.google.zxing.qrcode.detector;\r
\r
+import com.google.zxing.DecodeHintType;\r
import com.google.zxing.MonochromeBitmapSource;\r
import com.google.zxing.ReaderException;\r
import com.google.zxing.ResultPoint;\r
import com.google.zxing.common.Collections;\r
import com.google.zxing.common.Comparator;\r
\r
+import java.util.Hashtable;\r
import java.util.Vector;\r
\r
/**\r
* <p>This class attempts to find finder patterns in a QR Code. Finder patterns are the square\r
* markers at three corners of a QR Code.</p>\r
*\r
- * <p>This class is not thread-safe and should not be reused.</p>\r
+ * <p>This class is thread-safe but not reentrant. Each thread must allocate its own object.\r
*\r
- * @author srowen@google.com (Sean Owen)\r
+ * @author Sean Owen\r
*/\r
-final class FinderPatternFinder {\r
+public class FinderPatternFinder {\r
\r
private static final int CENTER_QUORUM = 2;\r
- private static final int BIG_SKIP = 3;\r
+ protected static final int MIN_SKIP = 3; // 1 pixel/module times 3 modules/center\r
+ protected static final int MAX_MODULES = 57; // support up to version 10 for mobile clients\r
+ private static final int INTEGER_MATH_SHIFT = 8;\r
\r
private final MonochromeBitmapSource image;\r
private final Vector possibleCenters;\r
private boolean hasSkipped;\r
+ private final int[] crossCheckStateCount;\r
\r
/**\r
* <p>Creates a finder that will search the image for three finder patterns.</p>\r
*\r
* @param image image to search\r
*/\r
- FinderPatternFinder(MonochromeBitmapSource image) {\r
+ public FinderPatternFinder(MonochromeBitmapSource image) {\r
this.image = image;\r
this.possibleCenters = new Vector();\r
+ this.crossCheckStateCount = new int[5];\r
}\r
\r
- FinderPatternInfo find() throws ReaderException {\r
+ protected MonochromeBitmapSource getImage() {\r
+ return image;\r
+ }\r
+\r
+ protected Vector getPossibleCenters() {\r
+ return possibleCenters;\r
+ }\r
+\r
+ FinderPatternInfo find(Hashtable hints) throws ReaderException {\r
+ boolean tryHarder = hints != null && hints.containsKey(DecodeHintType.TRY_HARDER);\r
int maxI = image.getHeight();\r
int maxJ = image.getWidth();\r
// We are looking for black/white/black/white/black modules in\r
// 1:1:3:1:1 ratio; this tracks the number of such modules seen so far\r
- int[] stateCount = new int[5];\r
+\r
+ // Let's assume that the maximum version QR Code we support takes up 1/4 the height of the\r
+ // image, and then account for the center being 3 modules in size. This gives the smallest\r
+ // number of pixels the center could be, so skip this often. When trying harder, look for all\r
+ // QR versions regardless of how dense they are.\r
+ int iSkip = (3 * maxI) / (4 * MAX_MODULES);\r
+ if (iSkip < MIN_SKIP || tryHarder) {\r
+ iSkip = MIN_SKIP;\r
+ }\r
+\r
boolean done = false;\r
- // We can afford to examine every few lines until we've started finding\r
- // the patterns\r
- int iSkip = BIG_SKIP;\r
+ int[] stateCount = new int[5];\r
+ BitArray blackRow = new BitArray(maxJ);\r
for (int i = iSkip - 1; i < maxI && !done; i += iSkip) {\r
// Get a row of black/white values\r
- BitArray blackRow = image.getBlackRow(i, null, 0, maxJ);\r
+ blackRow = image.getBlackRow(i, blackRow, 0, maxJ);\r
stateCount[0] = 0;\r
stateCount[1] = 0;\r
stateCount[2] = 0;\r
if (foundPatternCross(stateCount)) { // Yes\r
boolean confirmed = handlePossibleCenter(stateCount, i, j);\r
if (confirmed) {\r
- iSkip = 1; // Go back to examining each line\r
+ // Start examining every other line. Checking each line turned out to be too\r
+ // expensive and didn't improve performance.\r
+ iSkip = 2;\r
if (hasSkipped) {\r
- done = haveMulitplyConfirmedCenters();\r
+ done = haveMultiplyConfirmedCenters();\r
} else {\r
int rowSkip = findRowSkip();\r
if (rowSkip > stateCount[2]) {\r
iSkip = stateCount[0];\r
if (hasSkipped) {\r
// Found a third one\r
- done = haveMulitplyConfirmedCenters();\r
+ done = haveMultiplyConfirmedCenters();\r
}\r
}\r
}\r
}\r
\r
FinderPattern[] patternInfo = selectBestPatterns();\r
- patternInfo = orderBestPatterns(patternInfo);\r
- float totalModuleSize = 0.0f;\r
- for (int i = 0; i < patternInfo.length; i++) {\r
- totalModuleSize += patternInfo[i].getEstimatedModuleSize();\r
- }\r
+ ResultPoint.orderBestPatterns(patternInfo);\r
\r
- return new FinderPatternInfo(totalModuleSize / (float) patternInfo.length, patternInfo);\r
+ return new FinderPatternInfo(patternInfo);\r
}\r
\r
/**\r
\r
/**\r
* @param stateCount count of black/white/black/white/black pixels just read\r
- * @return true iff the proportions of the counts is close enough to the 1/13/1/1 ratios\r
- * used by finder patterns to be considered a match\r
+ * @return true iff the proportions of the counts is close enough to the 1/1/3/1/1 ratios\r
+ * used by finder patterns to be considered a match\r
*/\r
- private static boolean foundPatternCross(int[] stateCount) {\r
+ protected static boolean foundPatternCross(int[] stateCount) {\r
int totalModuleSize = 0;\r
for (int i = 0; i < 5; i++) {\r
- if (stateCount[i] == 0) {\r
+ int count = stateCount[i];\r
+ if (count == 0) {\r
return false;\r
}\r
- totalModuleSize += stateCount[i];\r
+ totalModuleSize += count;\r
}\r
if (totalModuleSize < 7) {\r
return false;\r
}\r
- float moduleSize = (float) totalModuleSize / 7.0f;\r
- float maxVariance = moduleSize / 2.5f;\r
- // Allow less than 40% variance from 1-1-3-1-1 proportions\r
- return Math.abs(moduleSize - stateCount[0]) < maxVariance &&\r
- Math.abs(moduleSize - stateCount[1]) < maxVariance &&\r
- Math.abs(3.0f * moduleSize - stateCount[2]) < 3.0f * maxVariance &&\r
- Math.abs(moduleSize - stateCount[3]) < maxVariance &&\r
- Math.abs(moduleSize - stateCount[4]) < maxVariance;\r
+ int moduleSize = (totalModuleSize << INTEGER_MATH_SHIFT) / 7;\r
+ int maxVariance = moduleSize / 2;\r
+ // Allow less than 50% variance from 1-1-3-1-1 proportions\r
+ return Math.abs(moduleSize - (stateCount[0] << INTEGER_MATH_SHIFT)) < maxVariance &&\r
+ Math.abs(moduleSize - (stateCount[1] << INTEGER_MATH_SHIFT)) < maxVariance &&\r
+ Math.abs(3 * moduleSize - (stateCount[2] << INTEGER_MATH_SHIFT)) < 3 * maxVariance &&\r
+ Math.abs(moduleSize - (stateCount[3] << INTEGER_MATH_SHIFT)) < maxVariance &&\r
+ Math.abs(moduleSize - (stateCount[4] << INTEGER_MATH_SHIFT)) < maxVariance;\r
+ }\r
+\r
+ private int[] getCrossCheckStateCount() {\r
+ crossCheckStateCount[0] = 0;\r
+ crossCheckStateCount[1] = 0;\r
+ crossCheckStateCount[2] = 0;\r
+ crossCheckStateCount[3] = 0;\r
+ crossCheckStateCount[4] = 0;\r
+ return crossCheckStateCount;\r
}\r
\r
/**\r
* @param startI row where a finder pattern was detected\r
* @param centerJ center of the section that appears to cross a finder pattern\r
* @param maxCount maximum reasonable number of modules that should be\r
- * observed in any reading state, based on the results of the horizontal scan\r
+ * observed in any reading state, based on the results of the horizontal scan\r
* @return vertical center of finder pattern, or {@link Float#NaN} if not found\r
*/\r
- private float crossCheckVertical(int startI, int centerJ, int maxCount) {\r
+ private float crossCheckVertical(int startI, int centerJ, int maxCount, int originalStateCountTotal) {\r
MonochromeBitmapSource image = this.image;\r
\r
int maxI = image.getHeight();\r
- int[] stateCount = new int[5];\r
+ int[] stateCount = getCrossCheckStateCount();\r
\r
// Start counting up from center\r
int i = startI;\r
stateCount[0]++;\r
i--;\r
}\r
- if (i < 0 || stateCount[0] > maxCount) {\r
+ if (stateCount[0] > maxCount) {\r
return Float.NaN;\r
}\r
\r
return Float.NaN;\r
}\r
\r
+ // If we found a finder-pattern-like section, but its size is more than 20% different than\r
+ // the original, assume it's a false positive\r
+ int stateCountTotal = stateCount[0] + stateCount[1] + stateCount[2] + stateCount[3] + stateCount[4];\r
+ if (5 * Math.abs(stateCountTotal - originalStateCountTotal) >= originalStateCountTotal) {\r
+ return Float.NaN;\r
+ }\r
+\r
return foundPatternCross(stateCount) ? centerFromEnd(stateCount, i) : Float.NaN;\r
}\r
\r
/**\r
- * <p>Like {@link #crossCheckVertical(int, int, int)}, and in fact is basically identical,\r
+ * <p>Like {@link #crossCheckVertical(int, int, int, int)}, and in fact is basically identical,\r
* except it reads horizontally instead of vertically. This is used to cross-cross\r
* check a vertical cross check and locate the real center of the alignment pattern.</p>\r
*/\r
- private float crossCheckHorizontal(int startJ, int centerI, int maxCount) {\r
+ private float crossCheckHorizontal(int startJ, int centerI, int maxCount, int originalStateCountTotal) {\r
MonochromeBitmapSource image = this.image;\r
\r
int maxJ = image.getWidth();\r
- int[] stateCount = new int[5];\r
+ int[] stateCount = getCrossCheckStateCount();\r
\r
int j = startJ;\r
while (j >= 0 && image.isBlack(j, centerI)) {\r
stateCount[0]++;\r
j--;\r
}\r
- if (j < 0 || stateCount[0] > maxCount) {\r
+ if (stateCount[0] > maxCount) {\r
return Float.NaN;\r
}\r
\r
return Float.NaN;\r
}\r
\r
+ // If we found a finder-pattern-like section, but its size is significantly different than\r
+ // the original, assume it's a false positive\r
+ int stateCountTotal = stateCount[0] + stateCount[1] + stateCount[2] + stateCount[3] + stateCount[4];\r
+ if (5 * Math.abs(stateCountTotal - originalStateCountTotal) >= originalStateCountTotal) {\r
+ return Float.NaN;\r
+ }\r
+\r
return foundPatternCross(stateCount) ? centerFromEnd(stateCount, j) : Float.NaN;\r
}\r
\r
* @param j end of possible finder pattern in row\r
* @return true if a finder pattern candidate was found this time\r
*/\r
- private boolean handlePossibleCenter(int[] stateCount,\r
+ protected boolean handlePossibleCenter(int[] stateCount,\r
int i,\r
int j) {\r
+ int stateCountTotal = stateCount[0] + stateCount[1] + stateCount[2] + stateCount[3] + stateCount[4];\r
float centerJ = centerFromEnd(stateCount, j);\r
- float centerI = crossCheckVertical(i, (int) centerJ, stateCount[2]);\r
+ float centerI = crossCheckVertical(i, (int) centerJ, stateCount[2], stateCountTotal);\r
if (!Float.isNaN(centerI)) {\r
// Re-cross check\r
- centerJ = crossCheckHorizontal((int) centerJ, (int) centerI, stateCount[2]);\r
+ centerJ = crossCheckHorizontal((int) centerJ, (int) centerI, stateCount[2], stateCountTotal);\r
if (!Float.isNaN(centerJ)) {\r
- float estimatedModuleSize =\r
- (float) (stateCount[0] + stateCount[1] + stateCount[2] + stateCount[3] + stateCount[4]) / 7.0f;\r
+ float estimatedModuleSize = (float) stateCountTotal / 7.0f;\r
boolean found = false;\r
int max = possibleCenters.size();\r
for (int index = 0; index < max; index++) {\r
\r
/**\r
* @return number of rows we could safely skip during scanning, based on the first\r
- * two finder patterns that have been located. In some cases their position will\r
- * allow us to infer that the third pattern must lie below a certain point farther\r
- * down in the image.\r
+ * two finder patterns that have been located. In some cases their position will\r
+ * allow us to infer that the third pattern must lie below a certain point farther\r
+ * down in the image.\r
*/\r
private int findRowSkip() {\r
int max = possibleCenters.size();\r
// How far down can we skip before resuming looking for the next\r
// pattern? In the worst case, only the difference between the\r
// difference in the x / y coordinates of the two centers.\r
- // This is the case where you find top left first. Draw it out.\r
+ // This is the case where you find top left last.\r
hasSkipped = true;\r
- return (int) Math.abs(Math.abs(firstConfirmedCenter.getX() - center.getX()) -\r
- Math.abs(firstConfirmedCenter.getY() - center.getY()));\r
+ return (int) (Math.abs(firstConfirmedCenter.getX() - center.getX()) -\r
+ Math.abs(firstConfirmedCenter.getY() - center.getY())) / 2;\r
}\r
}\r
}\r
\r
/**\r
* @return true iff we have found at least 3 finder patterns that have been detected\r
- * at least {@link #CENTER_QUORUM} times each\r
+ * at least {@link #CENTER_QUORUM} times each, and, the estimated module size of the\r
+ * candidates is "pretty similar"\r
*/\r
- private boolean haveMulitplyConfirmedCenters() {\r
- int count = 0;\r
+ private boolean haveMultiplyConfirmedCenters() {\r
+ int confirmedCount = 0;\r
+ float totalModuleSize = 0.0f;\r
int max = possibleCenters.size();\r
for (int i = 0; i < max; i++) {\r
- if (((FinderPattern) possibleCenters.elementAt(i)).getCount() >= CENTER_QUORUM) {\r
- if (++count == 3) {\r
- return true;\r
- }\r
+ FinderPattern pattern = (FinderPattern) possibleCenters.elementAt(i);\r
+ if (pattern.getCount() >= CENTER_QUORUM) {\r
+ confirmedCount++;\r
+ totalModuleSize += pattern.getEstimatedModuleSize();\r
}\r
}\r
- return false;\r
+ if (confirmedCount < 3) {\r
+ return false;\r
+ }\r
+ // OK, we have at least 3 confirmed centers, but, it's possible that one is a "false positive"\r
+ // and that we need to keep looking. We detect this by asking if the estimated module sizes\r
+ // vary too much. We arbitrarily say that when the total deviation from average exceeds\r
+ // 15% of the total module size estimates, it's too much.\r
+ float average = totalModuleSize / (float) max;\r
+ float totalDeviation = 0.0f;\r
+ for (int i = 0; i < max; i++) {\r
+ FinderPattern pattern = (FinderPattern) possibleCenters.elementAt(i);\r
+ totalDeviation += Math.abs(pattern.getEstimatedModuleSize() - average);\r
+ }\r
+ return totalDeviation <= 0.05f * totalModuleSize;\r
}\r
\r
/**\r
* @return the 3 best {@link FinderPattern}s from our list of candidates. The "best" are\r
- * those that have been detected at least {@link #CENTER_QUORUM} times, and whose module\r
- * size differs from the average among those patterns the least\r
+ * those that have been detected at least {@link #CENTER_QUORUM} times, and whose module\r
+ * size differs from the average among those patterns the least\r
* @throws ReaderException if 3 such finder patterns do not exist\r
*/\r
private FinderPattern[] selectBestPatterns() throws ReaderException {\r
\r
if (size < 3) {\r
// Couldn't find enough finder patterns\r
- throw new ReaderException("Could not find three finder patterns");\r
- }\r
-\r
- if (size == 3) {\r
- // Found just enough -- hope these are good!\r
- return new FinderPattern[] {\r
- (FinderPattern) possibleCenters.elementAt(0),\r
- (FinderPattern) possibleCenters.elementAt(1),\r
- (FinderPattern) possibleCenters.elementAt(2) \r
- };\r
+ throw ReaderException.getInstance();\r
}\r
\r
- possibleCenters.setSize(size);\r
-\r
- // Hmm, multiple found. We need to pick the best three. Find the most\r
- // popular ones whose module size is nearest the average\r
-\r
- float averageModuleSize = 0.0f;\r
- for (int i = 0; i < size; i++) {\r
- averageModuleSize += ((FinderPattern) possibleCenters.elementAt(i)).getEstimatedModuleSize();\r
+ if (size > 3) {\r
+ // Throw away all but those first size candidate points we found.\r
+ possibleCenters.setSize(size);\r
+ // We need to pick the best three. Find the most\r
+ // popular ones whose module size is nearest the average\r
+ float averageModuleSize = 0.0f;\r
+ for (int i = 0; i < size; i++) {\r
+ averageModuleSize += ((FinderPattern) possibleCenters.elementAt(i)).getEstimatedModuleSize();\r
+ }\r
+ averageModuleSize /= (float) size;\r
+ // We don't have java.util.Collections in J2ME\r
+ Collections.insertionSort(possibleCenters, new ClosestToAverageComparator(averageModuleSize));\r
}\r
- averageModuleSize /= (float) size;\r
-\r
- // We don't have java.util.Collections in J2ME\r
- Collections.insertionSort(possibleCenters, new ClosestToAverageComparator(averageModuleSize));\r
\r
- return new FinderPattern[] {\r
- (FinderPattern) possibleCenters.elementAt(0),\r
- (FinderPattern) possibleCenters.elementAt(1),\r
- (FinderPattern) possibleCenters.elementAt(2)\r
+ return new FinderPattern[]{\r
+ (FinderPattern) possibleCenters.elementAt(0),\r
+ (FinderPattern) possibleCenters.elementAt(1),\r
+ (FinderPattern) possibleCenters.elementAt(2)\r
};\r
}\r
\r
- /**\r
- * <p>Having found three "best" finder patterns we need to decide which is the top-left, top-right,\r
- * bottom-left. We assume that the one closest to the other two is the top-left one; this is not\r
- * strictly true (imagine extreme perspective distortion) but for the moment is a serviceable assumption.\r
- * Lastly we sort top-right from bottom-left by figuring out orientation from vector cross products.</p>\r
- *\r
- * @param patterns three best {@link FinderPattern}s\r
- * @return same {@link FinderPattern}s ordered bottom-left, top-left, top-right\r
- */\r
- private static FinderPattern[] orderBestPatterns(FinderPattern[] patterns) {\r
-\r
- // Find distances between pattern centers\r
- float abDistance = distance(patterns[0], patterns[1]);\r
- float bcDistance = distance(patterns[1], patterns[2]);\r
- float acDistance = distance(patterns[0], patterns[2]);\r
-\r
- FinderPattern topLeft;\r
- FinderPattern topRight;\r
- FinderPattern bottomLeft;\r
- // Assume one closest to other two is top left;\r
- // topRight and bottomLeft will just be guesses below at first\r
- if (bcDistance >= abDistance && bcDistance >= acDistance) {\r
- topLeft = patterns[0];\r
- topRight = patterns[1];\r
- bottomLeft = patterns[2];\r
- } else if (acDistance >= bcDistance && acDistance >= abDistance) {\r
- topLeft = patterns[1];\r
- topRight = patterns[0];\r
- bottomLeft = patterns[2];\r
- } else {\r
- topLeft = patterns[2];\r
- topRight = patterns[0];\r
- bottomLeft = patterns[1];\r
- }\r
-\r
- // Use cross product to figure out which of other1/2 is the bottom left\r
- // pattern. The vector "top-left -> bottom-left" x "top-left -> top-right"\r
- // should yield a vector with positive z component\r
- if ((bottomLeft.getY() - topLeft.getY()) * (topRight.getX() - topLeft.getX()) <\r
- (bottomLeft.getX() - topLeft.getX()) * (topRight.getY() - topLeft.getY())) {\r
- FinderPattern temp = topRight;\r
- topRight = bottomLeft;\r
- bottomLeft = temp;\r
- }\r
-\r
- return new FinderPattern[] {bottomLeft, topLeft, topRight};\r
- }\r
-\r
- /**\r
- * @return distance between two points\r
- */\r
- static float distance(ResultPoint pattern1, ResultPoint pattern2) {\r
- float xDiff = pattern1.getX() - pattern2.getX();\r
- float yDiff = pattern1.getY() - pattern2.getY();\r
- return (float) Math.sqrt((double) (xDiff * xDiff + yDiff * yDiff));\r
- }\r
-\r
/**\r
* <p>Orders by {@link FinderPattern#getCount()}, descending.</p>\r
*/\r
*/\r
private static class ClosestToAverageComparator implements Comparator {\r
private final float averageModuleSize;\r
+\r
private ClosestToAverageComparator(float averageModuleSize) {\r
this.averageModuleSize = averageModuleSize;\r
}\r
+\r
public int compare(Object center1, Object center2) {\r
return Math.abs(((FinderPattern) center1).getEstimatedModuleSize() - averageModuleSize) <\r
- Math.abs(((FinderPattern) center2).getEstimatedModuleSize() - averageModuleSize) ?\r
- -1 :\r
- 1;\r
+ Math.abs(((FinderPattern) center2).getEstimatedModuleSize() - averageModuleSize) ?\r
+ -1 :\r
+ 1;\r
}\r
}\r
\r
projects / zxing.git / blobdiff