private void process(Gray8Image in, BilevelImage out) {
final int HEIGHT = in.getHeight();
final int WIDTH = in.getWidth();
if (out == null) {
out = new MemoryBilevelImage(WIDTH, HEIGHT);
}
final int NUM_ERROR_PIXELS = errorNum.length;
// create buffer
int[] buffer = new int[newWidth * numRows];
// System.out.println("buffer length=" + buffer.length);
// fill buffer with numRows (or HEIGHT, whatever is smaller) rows of data
int n = Math.min(numRows, HEIGHT);
int offset = leftColumns;
int bufferYIndex = 0;
while (n-- > 0) {
fillBuffer(0, bufferYIndex++, buffer, offset);
offset += newWidth;
}
int bufferLastRowOffset = offset - newWidth;
// set complete output image to black
out.clear(BilevelImage.BLACK);
for (int y = 0; y < HEIGHT; y++) {
int bufferIndex = leftColumns;
for (int x = 0; x < WIDTH; x++) {
int value = buffer[bufferIndex];
if (value < 0) {
value = 0;
} else if (value > 255) {
value = 255;
}
int error;
if ((value & 0x80) == 0) {
// black pixel need not be written to output image
// because all of its pixels have initially been set
// to that color
error = value;
} else {
// white
out.putWhite(x, y);
error = value - 255;
}
for (int i = 0; i < NUM_ERROR_PIXELS; i++) {
int errorPart = error * errorNum[i] / errorDen[i];
buffer[bufferIndex + indexLut[i]] += errorPart;
}
bufferIndex++;
}
for (int i = 0, j = newWidth; j < buffer.length; i++, j++) {
buffer[i] = buffer[j];
}
if (bufferYIndex < HEIGHT) {
fillBuffer(0, bufferYIndex++, buffer, bufferLastRowOffset);
}
setProgress(y, HEIGHT);
}
setOutputImage(out);
}
/**
* Returns the number of black and white differences between the template and exam file.
*
* @param img Image of exams
* @param x x start coordinate of the file
* @param y y start coordinate of the file
* @param template Template of exams
* @param dump Dump to screen
* @return The difference
*/
public static double templateXOR(
Gray8Image img, int x, int y, Gray8Image template, boolean dump) {
int diff = 0, total = 0;
for (int j = y; j < y + template.getHeight() && j < img.getHeight(); j++) {
for (int i = x; i < x + template.getWidth() && i < img.getWidth(); i++) {
// XXX
boolean isblack = (img.getSample(i, j) < 200 ? true : false);
// if(dump) { System.out.print((isblack
// & template.isWhite(i - x, j - y) ? "1" : ((!isblack)
// & template.isBlack(i - x, j - y)) ? "-" : "0")); }
if ((isblack & template.isWhite(i - x, j - y)
| (!isblack) & template.isBlack(i - x, j - y))) {
diff++;
}
total++;
}
// if(dump) { System.out.println(); }
}
return ((double) diff) / total;
}
private void fillTemplate(
Gray8Image templateimg, double outerdiamX, double innerdiamX, double aspect) {
double centerX = templateimg.getWidth() / 2;
double centerY = templateimg.getHeight() / 2;
double outerrad = outerdiamX / 2;
double innerrad = innerdiamX / 2;
for (int wCount = 0; wCount < templateimg.getWidth(); wCount++) {
for (int hCount = 0; hCount < templateimg.getHeight(); hCount++) {
double dist =
Math.sqrt(
(wCount - centerX) * (wCount - centerX)
+ (hCount - centerY) / aspect * (hCount - centerY) / aspect);
if (dist <= outerrad && dist > innerrad) {
templateimg.putBlack(wCount, hCount);
} else {
templateimg.putWhite(wCount, hCount);
}
}
}
}
private void process(Gray8Image in, Gray8Image out) {
final int HEIGHT = in.getHeight();
final int WIDTH = in.getWidth();
final int RIGHT_SHIFT = 8 - grayBits;
final int[] GRAY_LUT = new int[1 << grayBits];
for (int i = 0; i < GRAY_LUT.length; i++) {
GRAY_LUT[i] = i * 255 / (GRAY_LUT.length - 1);
}
if (out == null) {
out = new MemoryGray8Image(WIDTH, HEIGHT);
}
final int NUM_ERROR_PIXELS = errorNum.length;
// create buffer
int[] buffer = new int[newWidth * numRows];
// fill buffer with numRows (or HEIGHT, whatever is smaller) rows of data
int n = Math.min(numRows, HEIGHT);
int offset = leftColumns;
int bufferYIndex = 0;
while (n-- > 0) {
fillBuffer(0, bufferYIndex++, buffer, offset);
offset += newWidth;
}
int bufferLastRowOffset = offset - newWidth;
for (int y = 0; y < HEIGHT; y++) {
int bufferIndex = leftColumns;
for (int x = 0; x < WIDTH; x++) {
int value = buffer[bufferIndex];
if (value < 0) {
value = 0;
} else if (value > 255) {
value = 255;
}
int quantized = GRAY_LUT[value >> RIGHT_SHIFT];
out.putSample(0, x, y, quantized);
int error = value - quantized;
for (int i = 0; i < NUM_ERROR_PIXELS; i++) {
int errorPart = error * errorNum[i] / errorDen[i];
buffer[bufferIndex + indexLut[i]] += errorPart;
}
bufferIndex++;
}
for (int i = 0, j = newWidth; j < buffer.length; i++, j++) {
buffer[i] = buffer[j];
}
if (bufferYIndex < HEIGHT) {
fillBuffer(0, bufferYIndex++, buffer, bufferLastRowOffset);
}
setProgress(y, HEIGHT);
}
setOutputImage(out);
}
private void fitTemplate() {
int startX = 0, startY = 0;
int endX = img.getWidth() - bestfit.getTemplate().getWidth();
int endY = img.getHeight() - bestfit.getTemplate().getHeight();
centerTemplate(startX, startY, endX, endY, 3);
templateXOR(img, bestfit.getX(), bestfit.getY(), bestfit.getTemplate(), true);
sizeTemplate();
aspectTemplate();
shiftTemplate();
sizeTemplate();
aspectTemplate();
shiftTemplate();
templateXOR(img, bestfit.getX(), bestfit.getY(), bestfit.getTemplate(), true);
}
private void centerTemplate(int startX, int startY, int endX, int endY, int granularity) {
int stepX = bestfit.getTemplate().getWidth() / granularity;
int stepY = bestfit.getTemplate().getHeight() / granularity;
// System.out.println("stepX = " + stepX + ": stepY = " + stepY);
double maxsim = -1;
int simi = -1, simj = -1;
for (int iCount = startX; iCount <= endX; iCount += stepX) {
for (int jCount = startY; jCount <= endY; jCount += stepY) {
double currsim = 1.0 - templateXOR(img, iCount, jCount, bestfit.getTemplate(), false);
// System.out.println(i + ":" + j + ":" + currsim);
if (maxsim == -1 || maxsim < currsim) {
maxsim = currsim;
simi = iCount;
simj = jCount;
}
}
}
// System.out.println("--- maxsim = " + maxsim + ":"
// + simi + ":" + simj);
if (maxsim > 0.5) {
if (stepX >= 4) { // up to an accuracy of 2 pixels
centerTemplate(
Math.max(simi - stepX / 2, 0),
Math.max(simj - stepY / 2, 0),
Math.min(simi + stepX / 2, img.getWidth()),
Math.min(simj + stepY / 2, img.getHeight()),
granularity * 2);
} else {
bestfit.setX(simi);
bestfit.setY(simj);
bestfit.setSim(maxsim);
}
}
}