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.common.BitArray;\r
+import com.google.zxing.NotFoundException;\r
+import com.google.zxing.ResultPoint;\r
+import com.google.zxing.ResultPointCallback;\r
+import com.google.zxing.common.BitMatrix;\r
import com.google.zxing.common.Collections;\r
import com.google.zxing.common.Comparator;\r
-import com.google.zxing.common.GenericResultPoint;\r
\r
import java.util.Hashtable;\r
import java.util.Vector;\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 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 MIN_SKIP = 3; // 1 pixel/module times 3 modules/center\r
- private static final int MAX_MODULES = 57; // support up to version 10 for mobile clients\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 BitMatrix image;\r
private final Vector possibleCenters;\r
private boolean hasSkipped;\r
private final int[] crossCheckStateCount;\r
+ private final ResultPointCallback resultPointCallback;\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(BitMatrix image) {\r
+ this(image, null);\r
+ }\r
+\r
+ public FinderPatternFinder(BitMatrix image, ResultPointCallback resultPointCallback) {\r
this.image = image;\r
this.possibleCenters = new Vector();\r
this.crossCheckStateCount = new int[5];\r
+ this.resultPointCallback = resultPointCallback;\r
+ }\r
+\r
+ protected BitMatrix getImage() {\r
+ return image;\r
}\r
\r
- FinderPatternInfo find(Hashtable hints) throws ReaderException {\r
+ protected Vector getPossibleCenters() {\r
+ return possibleCenters;\r
+ }\r
+\r
+ FinderPatternInfo find(Hashtable hints) throws NotFoundException {\r
boolean tryHarder = hints != null && hints.containsKey(DecodeHintType.TRY_HARDER);\r
int maxI = image.getHeight();\r
int maxJ = image.getWidth();\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 = (int) (maxI / (MAX_MODULES * 4.0f) * 3);\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
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
- blackRow = image.getBlackRow(i, blackRow, 0, maxJ);\r
stateCount[0] = 0;\r
stateCount[1] = 0;\r
stateCount[2] = 0;\r
stateCount[4] = 0;\r
int currentState = 0;\r
for (int j = 0; j < maxJ; j++) {\r
- if (blackRow.get(j)) {\r
+ if (image.get(j, i)) {\r
// Black pixel\r
if ((currentState & 1) == 1) { // Counting white pixels\r
currentState++;\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
}\r
}\r
} else {\r
- // Advance to next black pixel\r
- do {\r
- j++;\r
- } while (j < maxJ && !blackRow.get(j));\r
- j--; // back up to that last white pixel\r
+ stateCount[0] = stateCount[2];\r
+ stateCount[1] = stateCount[3];\r
+ stateCount[2] = stateCount[4];\r
+ stateCount[3] = 1;\r
+ stateCount[4] = 0;\r
+ currentState = 3;\r
+ continue;\r
}\r
// Clear state to start looking again\r
currentState = 0;\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
- GenericResultPoint.orderBestPatterns(patternInfo);\r
+ ResultPoint.orderBestPatterns(patternInfo);\r
\r
return new FinderPatternInfo(patternInfo);\r
}\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
int count = stateCount[i];\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, int originalStateCountTotal) {\r
- MonochromeBitmapSource image = this.image;\r
+ private float crossCheckVertical(int startI, int centerJ, int maxCount,\r
+ int originalStateCountTotal) {\r
+ BitMatrix image = this.image;\r
\r
int maxI = image.getHeight();\r
int[] stateCount = getCrossCheckStateCount();\r
\r
// Start counting up from center\r
int i = startI;\r
- while (i >= 0 && image.isBlack(centerJ, i)) {\r
+ while (i >= 0 && image.get(centerJ, i)) {\r
stateCount[2]++;\r
i--;\r
}\r
if (i < 0) {\r
return Float.NaN;\r
}\r
- while (i >= 0 && !image.isBlack(centerJ, i) && stateCount[1] <= maxCount) {\r
+ while (i >= 0 && !image.get(centerJ, i) && stateCount[1] <= maxCount) {\r
stateCount[1]++;\r
i--;\r
}\r
if (i < 0 || stateCount[1] > maxCount) {\r
return Float.NaN;\r
}\r
- while (i >= 0 && image.isBlack(centerJ, i) && stateCount[0] <= maxCount) {\r
+ while (i >= 0 && image.get(centerJ, i) && stateCount[0] <= maxCount) {\r
stateCount[0]++;\r
i--;\r
}\r
\r
// Now also count down from center\r
i = startI + 1;\r
- while (i < maxI && image.isBlack(centerJ, i)) {\r
+ while (i < maxI && image.get(centerJ, i)) {\r
stateCount[2]++;\r
i++;\r
}\r
if (i == maxI) {\r
return Float.NaN;\r
}\r
- while (i < maxI && !image.isBlack(centerJ, i) && stateCount[3] < maxCount) {\r
+ while (i < maxI && !image.get(centerJ, i) && stateCount[3] < maxCount) {\r
stateCount[3]++;\r
i++;\r
}\r
if (i == maxI || stateCount[3] >= maxCount) {\r
return Float.NaN;\r
}\r
- while (i < maxI && image.isBlack(centerJ, i) && stateCount[4] < maxCount) {\r
+ while (i < maxI && image.get(centerJ, i) && stateCount[4] < maxCount) {\r
stateCount[4]++;\r
i++;\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
+ // If we found a finder-pattern-like section, but its size is more than 40% 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
+ int stateCountTotal = stateCount[0] + stateCount[1] + stateCount[2] + stateCount[3] +\r
+ stateCount[4];\r
+ if (5 * Math.abs(stateCountTotal - originalStateCountTotal) >= 2 * originalStateCountTotal) {\r
return Float.NaN;\r
}\r
\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, int originalStateCountTotal) {\r
- MonochromeBitmapSource image = this.image;\r
+ private float crossCheckHorizontal(int startJ, int centerI, int maxCount,\r
+ int originalStateCountTotal) {\r
+ BitMatrix image = this.image;\r
\r
int maxJ = image.getWidth();\r
int[] stateCount = getCrossCheckStateCount();\r
\r
int j = startJ;\r
- while (j >= 0 && image.isBlack(j, centerI)) {\r
+ while (j >= 0 && image.get(j, centerI)) {\r
stateCount[2]++;\r
j--;\r
}\r
if (j < 0) {\r
return Float.NaN;\r
}\r
- while (j >= 0 && !image.isBlack(j, centerI) && stateCount[1] <= maxCount) {\r
+ while (j >= 0 && !image.get(j, centerI) && stateCount[1] <= maxCount) {\r
stateCount[1]++;\r
j--;\r
}\r
if (j < 0 || stateCount[1] > maxCount) {\r
return Float.NaN;\r
}\r
- while (j >= 0 && image.isBlack(j, centerI) && stateCount[0] <= maxCount) {\r
+ while (j >= 0 && image.get(j, centerI) && stateCount[0] <= maxCount) {\r
stateCount[0]++;\r
j--;\r
}\r
}\r
\r
j = startJ + 1;\r
- while (j < maxJ && image.isBlack(j, centerI)) {\r
+ while (j < maxJ && image.get(j, centerI)) {\r
stateCount[2]++;\r
j++;\r
}\r
if (j == maxJ) {\r
return Float.NaN;\r
}\r
- while (j < maxJ && !image.isBlack(j, centerI) && stateCount[3] < maxCount) {\r
+ while (j < maxJ && !image.get(j, centerI) && stateCount[3] < maxCount) {\r
stateCount[3]++;\r
j++;\r
}\r
if (j == maxJ || stateCount[3] >= maxCount) {\r
return Float.NaN;\r
}\r
- while (j < maxJ && image.isBlack(j, centerI) && stateCount[4] < maxCount) {\r
+ while (j < maxJ && image.get(j, centerI) && stateCount[4] < maxCount) {\r
stateCount[4]++;\r
j++;\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
+ int stateCountTotal = stateCount[0] + stateCount[1] + stateCount[2] + stateCount[3] +\r
+ stateCount[4];\r
if (5 * Math.abs(stateCountTotal - originalStateCountTotal) >= originalStateCountTotal) {\r
return Float.NaN;\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
- int i,\r
- int j) {\r
- int stateCountTotal = stateCount[0] + stateCount[1] + stateCount[2] + stateCount[3] + stateCount[4];\r
+ protected boolean handlePossibleCenter(int[] stateCount, int i, int j) {\r
+ int stateCountTotal = stateCount[0] + stateCount[1] + stateCount[2] + stateCount[3] +\r
+ stateCount[4];\r
float centerJ = centerFromEnd(stateCount, j);\r
float centerI = crossCheckVertical(i, (int) centerJ, stateCount[2], stateCountTotal);\r
if (!Float.isNaN(centerI)) {\r
}\r
}\r
if (!found) {\r
- possibleCenters.addElement(new FinderPattern(centerJ, centerI, estimatedModuleSize));\r
+ ResultPoint point = new FinderPattern(centerJ, centerI, estimatedModuleSize);\r
+ possibleCenters.addElement(point);\r
+ if (resultPointCallback != null) {\r
+ resultPointCallback.foundPossibleResultPoint(point);\r
+ }\r
}\r
return true;\r
}\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(firstConfirmedCenter.getX() - center.getX()) -\r
- Math.abs(firstConfirmedCenter.getY() - center.getY()));\r
+ Math.abs(firstConfirmedCenter.getY() - center.getY())) / 2;\r
}\r
}\r
}\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
+ private boolean haveMultiplyConfirmedCenters() {\r
int confirmedCount = 0;\r
float totalModuleSize = 0.0f;\r
int max = possibleCenters.size();\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 / max;\r
+ // 5% 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 <= 0.15f * totalModuleSize;\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
- * @throws ReaderException if 3 such finder patterns do not exist\r
+ * @throws NotFoundException if 3 such finder patterns do not exist\r
*/\r
- private FinderPattern[] selectBestPatterns() throws ReaderException {\r
- Collections.insertionSort(possibleCenters, new CenterComparator());\r
- int size = 0;\r
- int max = possibleCenters.size();\r
- while (size < max) {\r
- if (((FinderPattern) possibleCenters.elementAt(size)).getCount() < CENTER_QUORUM) {\r
- break;\r
- }\r
- size++;\r
- }\r
+ private FinderPattern[] selectBestPatterns() throws NotFoundException {\r
\r
- if (size < 3) {\r
+ int startSize = possibleCenters.size();\r
+ if (startSize < 3) {\r
// Couldn't find enough finder patterns\r
- throw ReaderException.getInstance();\r
+ throw NotFoundException.getNotFoundInstance();\r
+ }\r
+\r
+ // Filter outlier possibilities whose module size is too different\r
+ if (startSize > 3) {\r
+ // But we can only afford to do so if we have at least 4 possibilities to choose from\r
+ float totalModuleSize = 0.0f;\r
+ float square = 0.0f;\r
+ for (int i = 0; i < startSize; i++) {\r
+ float size = ((FinderPattern) possibleCenters.elementAt(i)).getEstimatedModuleSize();\r
+ totalModuleSize += size;\r
+ square += size * size;\r
+ }\r
+ float average = totalModuleSize / (float) startSize;\r
+ float stdDev = (float) Math.sqrt(square / startSize - average * average);\r
+\r
+ Collections.insertionSort(possibleCenters, new FurthestFromAverageComparator(average));\r
+\r
+ float limit = Math.max(0.2f * average, stdDev);\r
+\r
+ for (int i = 0; i < possibleCenters.size() && possibleCenters.size() > 3; i++) {\r
+ FinderPattern pattern = (FinderPattern) possibleCenters.elementAt(i);\r
+ if (Math.abs(pattern.getEstimatedModuleSize() - average) > limit) {\r
+ possibleCenters.removeElementAt(i);\r
+ i--;\r
+ }\r
+ }\r
}\r
\r
- if (size > 3) {\r
+ if (possibleCenters.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
+ float totalModuleSize = 0.0f;\r
+ for (int i = 0; i < possibleCenters.size(); i++) {\r
+ totalModuleSize += ((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
+ float average = totalModuleSize / (float) possibleCenters.size();\r
+\r
+ Collections.insertionSort(possibleCenters, new CenterComparator(average));\r
+\r
+ possibleCenters.setSize(3);\r
}\r
\r
return new FinderPattern[]{\r
}\r
\r
/**\r
- * <p>Orders by {@link FinderPattern#getCount()}, descending.</p>\r
+ * <p>Orders by furthest from average</p>\r
*/\r
- private static class CenterComparator implements Comparator {\r
+ private static class FurthestFromAverageComparator implements Comparator {\r
+ private final float average;\r
+ private FurthestFromAverageComparator(float f) {\r
+ average = f;\r
+ }\r
public int compare(Object center1, Object center2) {\r
- return ((FinderPattern) center2).getCount() - ((FinderPattern) center1).getCount();\r
+ float dA = Math.abs(((FinderPattern) center2).getEstimatedModuleSize() - average);\r
+ float dB = Math.abs(((FinderPattern) center1).getEstimatedModuleSize() - average);\r
+ return dA < dB ? -1 : (dA == dB ? 0 : 1);\r
}\r
}\r
\r
/**\r
- * <p>Orders by variance from average module size, ascending.</p>\r
+ * <p>Orders by {@link FinderPattern#getCount()}, descending.</p>\r
*/\r
- private static class ClosestToAverageComparator implements Comparator {\r
- private final float averageModuleSize;\r
-\r
- private ClosestToAverageComparator(float averageModuleSize) {\r
- this.averageModuleSize = averageModuleSize;\r
+ private static class CenterComparator implements Comparator {\r
+ private final float average;\r
+ private CenterComparator(float f) {\r
+ average = f;\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
+ if (((FinderPattern) center2).getCount() == ((FinderPattern) center1).getCount()) {\r
+ float dA = Math.abs(((FinderPattern) center2).getEstimatedModuleSize() - average);\r
+ float dB = Math.abs(((FinderPattern) center1).getEstimatedModuleSize() - average);\r
+ return dA < dB ? 1 : (dA == dB ? 0 : -1);\r
+ } else {\r
+ return ((FinderPattern) center2).getCount() - ((FinderPattern) center1).getCount();\r
+ }\r
}\r
}\r
\r
projects / zxing.git / blobdiff