I'm developing an augmented reality application using the ARToolkit. I would like to add a feature where I would control an object's size, or control the volume of a played song, by rotating a specific marker. I've found an example of an application, which is returning a 4x4 matrix that contains position and rotation information of the marker.
An example of such a matrix:
000,1878 -000,9442 -000,2707 -002,2898
-000,6210 000,0994 -000,7775 117,8998
-000,7610 -000,3141 000,5677 -530,6667
000,0000 000,0000 000,0000 001,0000
I've found a formula and a corresponding java method for the decomposition of the matrix to all three rotation angles, but I'm confused by the returned angle values.
The java method:
/** this conversion uses conventions as described on page:
* http://www.euclideanspace.com/maths/geometry/rotations/euler/index.htm
* Coordinate System: right hand
* Positive angle: right hand
* Order of euler angles: heading first, then attitude, then bank
* matrix row column ordering:
* [m00 m01 m02]
* [m10 m11 m12]
* [m20 m21 m22]*/
public final void rotate(matrix m) {
// Assuming the angles are in radians.
if (m.m10 > 0.998) { // singularity at north pole
heading = Math.atan2(m.m02,m.m22);
attitude = Math.PI/2;
bank = 0;
return;
}
if (m.m10 < -0.998) { // singularity at south pole
heading = Math.atan2(m.m02,m.m22);
attitude = -Math.PI/2;
bank = 0;
return;
}
heading = Math.atan2(-m.m20,m.m00);
bank = Math.atan2(-m.m12,m.m11);
attitude = Math.asin(m.m10);
}
Example of the returned values:
Heading: 1.384716377951241,
Bank: 1.3919044985590532
Attitude: -0.7751361901097762
So the result, obviously, isn't in degrees, which I would want. I'm I doing this the right way? What am I doing wrong?
I'm currently writing a new Karaoke-FX-Generator using Java. Now I have a problem with the implementation of the TextExtents-Function: It returns the wrong string bounds for the Subtitle file.
Here's an example:
The red rectangle represents the bounds of the string calculated by my program while the red background are the bounds calculated by xy-vsfilter.
Does anyone know how to fix that. I'm trying several hours and I still don't get any further.
This is the current implementation of the function.
/**
* Calculates the text-extents for the given text in the specified
* style.
* #param style The style
* #param text The text
* #return The extents of the text.
*/
public TextExtents getTextExtents(AssStyle style, String text) {
// Reads the font object from the cache.
Font font = this.getFont(style.getFontname(), style.isBold(), style.isItalic());
// If the font is unknown, return null.
if (font == null)
return null;
// Add the font size. (Note: FONT_SIZE_SCALE is 64)
font = font.deriveFont((float) style.getFontsize() * FONT_SIZE_SCALE);
// Returns other values like ascend, descend and ext-lead.
LineMetrics metrics = font.getLineMetrics(text, this.ctx);
// Calculate String bounds.
Rectangle2D rSize = font.getStringBounds(text, this.ctx);
// Returns the text-extents.
return new TextExtents(
rSize.getWidth() / FONT_SIZE_SCALE,
rSize.getHeight() / FONT_SIZE_SCALE,
metrics.getAscent() / FONT_SIZE_SCALE,
metrics.getDescent() / FONT_SIZE_SCALE,
metrics.getLeading() / FONT_SIZE_SCALE
);
}
I partially solved the problem. LOGFONT.lfHeight and Java uses different unit for font sizes. As such, I had to convert the font-size of java to the "logical" units.
// I used this code to convert from pixel-size to "logical units"
float fontSize = 72F / SCREEN_DPI; // SCREEN_DPI = 96
Now I only have small differences.
This is my situation. It involves aligning a scanned image which will account for incorrect scanning. I must align the scanned image with my Java program.
These are more details:
There is a table-like form printed on a sheet of paper, which will be scanned into an image file.
I will open the picture with Java, and I will have an OVERLAY of text boxes.
The text boxes are supposed to align correctly with the scanned image.
In order to align correctly, my Java program must analyze the scanned image and detect the coordinates of the edges of the table on the scanned image, and thus position the image and the textboxes so that the textboxes and the image both align properly (in case of incorrect scanning)
You see, the guy scanning the image might not necessarily place the image in a perfectly correct position, so I need my program to automatically align the scanned image as it loads it. This program will be reusable on many of such scanned images, so I need the program to be flexible in this way.
My question is one of the following:
How can I use Java to detect the y coordinate of the upper edge of the table and the x-coordinate of the leftmost edge of the table. The table is a a regular table with many cells, with black thin border, printed on a white sheet of paper (horizontal printout)
If an easier method exists to automatically align the scanned image in such a way that all scanned images will have the graphical table align to the same x, y coordinates, then share this method :).
If you don't know the answer to the above to questions, do tell me where I should start. I don't know much about graphics java programming and I have about 1 month to finish this program. Just assume that I have a tight schedule and I have to make the graphics part as simple as possible for me.
Cheers and thank you.
Try to start from a simple scenario and then improve the approach.
Detect corners.
Find the corners in the boundaries of the form.
Using the form corners coordinates, calculate the rotation angle.
Rotate/scale the image.
Map the position of each field in the form relative to form origin coordinates.
Match the textboxes.
The program presented at the end of this post does the steps 1 to 3. It was implemented using Marvin Framework. The image below shows the output image with the detected corners.
The program also outputs: Rotation angle:1.6365770416167182
Source code:
import java.awt.Color;
import java.awt.Point;
import marvin.image.MarvinImage;
import marvin.io.MarvinImageIO;
import marvin.plugin.MarvinImagePlugin;
import marvin.util.MarvinAttributes;
import marvin.util.MarvinPluginLoader;
public class FormCorners {
public FormCorners(){
// Load plug-in
MarvinImagePlugin moravec = MarvinPluginLoader.loadImagePlugin("org.marvinproject.image.corner.moravec");
MarvinAttributes attr = new MarvinAttributes();
// Load image
MarvinImage image = MarvinImageIO.loadImage("./res/printedForm.jpg");
// Process and save output image
moravec.setAttribute("threshold", 2000);
moravec.process(image, null, attr);
Point[] boundaries = boundaries(attr);
image = showCorners(image, boundaries, 12);
MarvinImageIO.saveImage(image, "./res/printedForm_output.jpg");
// Print rotation angle
double angle = (Math.atan2((boundaries[1].y*-1)-(boundaries[0].y*-1),boundaries[1].x-boundaries[0].x) * 180 / Math.PI);
angle = angle >= 0 ? angle : angle + 360;
System.out.println("Rotation angle:"+angle);
}
private Point[] boundaries(MarvinAttributes attr){
Point upLeft = new Point(-1,-1);
Point upRight = new Point(-1,-1);
Point bottomLeft = new Point(-1,-1);
Point bottomRight = new Point(-1,-1);
double ulDistance=9999,blDistance=9999,urDistance=9999,brDistance=9999;
double tempDistance=-1;
int[][] cornernessMap = (int[][]) attr.get("cornernessMap");
for(int x=0; x<cornernessMap.length; x++){
for(int y=0; y<cornernessMap[0].length; y++){
if(cornernessMap[x][y] > 0){
if((tempDistance = Point.distance(x, y, 0, 0)) < ulDistance){
upLeft.x = x; upLeft.y = y;
ulDistance = tempDistance;
}
if((tempDistance = Point.distance(x, y, cornernessMap.length, 0)) < urDistance){
upRight.x = x; upRight.y = y;
urDistance = tempDistance;
}
if((tempDistance = Point.distance(x, y, 0, cornernessMap[0].length)) < blDistance){
bottomLeft.x = x; bottomLeft.y = y;
blDistance = tempDistance;
}
if((tempDistance = Point.distance(x, y, cornernessMap.length, cornernessMap[0].length)) < brDistance){
bottomRight.x = x; bottomRight.y = y;
brDistance = tempDistance;
}
}
}
}
return new Point[]{upLeft, upRight, bottomRight, bottomLeft};
}
private MarvinImage showCorners(MarvinImage image, Point[] points, int rectSize){
MarvinImage ret = image.clone();
for(Point p:points){
ret.fillRect(p.x-(rectSize/2), p.y-(rectSize/2), rectSize, rectSize, Color.red);
}
return ret;
}
public static void main(String[] args) {
new FormCorners();
}
}
Edge detection is something that is typically done by enhancing the contrast between neighboring pixels, such that you get a easily detectable line, which is suitable for further processing.
To do this, a "kernel" transforms a pixel according it the pixel's inital value, and the value of that pixel's neighbors. A good edge detection kernel will enhance the differences between neighboring pixels, and reduce the strength of a pixel with similar neigbors.
I would start by looking at the Sobel operator. This might not return results that are immediately useful to you; however, it will get you far closer than you would be if you were to approach the problem with little knowledge of the field.
After you have some crisp clean edges, you can use larger kernels to detect points where it seems that a 90% bend in two lines occurs, that might give you the pixel coordinates of the outer rectangle, which might be enough for your purposes.
With those outer coordinates, it still is a bit of math to make the new pixels be composted with the average values between the old pixels rotated and moved to "match". The results (especially if you do not know about anti-aliasing math) can be pretty bad, adding blur to the image.
Sharpening filters might be a solution, but they come with their own issues, mainly they make the picture sharper by adding graininess. Too much, and it is obvious that the original image is not a high-quality scan.
I researched the libraries but in the end I found it more convenient to code up my own edge detection methods.
The class below will detect black/grayed out edges of a scanned sheet of paper that contains such edges, and will return the x and y coordinate of the edges of the sheet of paper, starting from the rightmost end (reverse = true) or from lower end (reverse = true) or from the top edge (reverse = false) or from left edge (reverse = false). Also...the program will take ranges along vertical edges (rangex) measured in pixels, and horizontal ranges (rangey) measured in pixels. The ranges determine outliers in the points received.
The program does 4 vertical cuts using the specified arrays, and 4 horizontal cuts. It retrieves the values of the dark dots. It uses the ranges to eliminate outliers. Sometimes, a little spot on the paper may cause an outlier point. The smaller the range, the fewer the outliers. However, sometimes the edge is slightly tilted, so you don't want to make the range too small.
Have fun. It works perfectly for me.
import java.awt.image.BufferedImage;
import java.awt.Color;
import java.util.ArrayList;
import java.lang.Math;
import java.awt.Point;
public class EdgeDetection {
public App ap;
public int[] horizontalCuts = {120, 220, 320, 420};
public int[] verticalCuts = {300, 350, 375, 400};
public void printEdgesTest(BufferedImage image, boolean reversex, boolean reversey, int rangex, int rangey){
int[] mx = horizontalCuts;
int[] my = verticalCuts;
//you are getting edge points here
//the "true" parameter indicates that it performs a cut starting at 0. (left edge)
int[] xEdges = getEdges(image, mx, reversex, true);
int edgex = getEdge(xEdges, rangex);
for(int x = 0; x < xEdges.length; x++){
System.out.println("EDGE = " + xEdges[x]);
}
System.out.println("THE EDGE = " + edgex);
//the "false" parameter indicates you are doing your cut starting at the end (image.getHeight)
//and ending at 0
//if the parameter was true, it would mean it would start the cuts at y = 0
int[] yEdges = getEdges(image, my, reversey, false);
int edgey = getEdge(yEdges, rangey);
for(int y = 0; y < yEdges.length; y++){
System.out.println("EDGE = " + yEdges[y]);
}
System.out.println("THE EDGE = " + edgey);
}
//This function takes an array of coordinates...detects outliers,
//and computes the average of non-outlier points.
public int getEdge(int[] edges, int range){
ArrayList<Integer> result = new ArrayList<Integer>();
boolean[] passes = new boolean[edges.length];
int[][] differences = new int[edges.length][edges.length-1];
//THIS CODE SEGMENT SAVES THE DIFFERENCES BETWEEN THE POINTS INTO AN ARRAY
for(int n = 0; n<edges.length; n++){
for(int m = 0; m<edges.length; m++){
if(m < n){
differences[n][m] = edges[n] - edges[m];
}else if(m > n){
differences[n][m-1] = edges[n] - edges[m];
}
}
}
//This array determines which points are outliers or nots (fall within range of other points)
for(int n = 0; n<edges.length; n++){
passes[n] = false;
for(int m = 0; m<edges.length-1; m++){
if(Math.abs(differences[n][m]) < range){
passes[n] = true;
System.out.println("EDGECHECK = TRUE" + n);
break;
}
}
}
//Create a new array only using valid points
for(int i = 0; i<edges.length; i++){
if(passes[i]){
result.add(edges[i]);
}
}
//Calculate the rounded mean... This will be the x/y coordinate of the edge
//Whether they are x or y values depends on the "reverse" variable used to calculate the edges array
int divisor = result.size();
int addend = 0;
double mean = 0;
for(Integer i : result){
addend += i;
}
mean = (double)addend/(double)divisor;
//returns the mean of the valid points: this is the x or y coordinate of your calculated edge.
if(mean - (int)mean >= .5){
System.out.println("MEAN " + mean);
return (int)mean+1;
}else{
System.out.println("MEAN " + mean);
return (int)mean;
}
}
//this function computes "dark" points, which include light gray, to detect edges.
//reverse - when true, starts counting from x = 0 or y = 0, and ends at image.getWidth or image.getHeight()
//verticalEdge - determines whether you want to detect a vertical edge, or a horizontal edge
//arr[] - determines the coordinates of the vertical or horizontal cuts you will do
//set the arr[] array according to the graphical layout of your scanned image
//image - this is the image you want to detect black/white edges of
public int[] getEdges(BufferedImage image, int[] arr, boolean reverse, boolean verticalEdge){
int red = 255;
int green = 255;
int blue = 255;
int[] result = new int[arr.length];
for(int n = 0; n<arr.length; n++){
for(int m = reverse ? (verticalEdge ? image.getWidth():image.getHeight())-1:0; reverse ? m>=0:m<(verticalEdge ? image.getWidth():image.getHeight());){
Color c = new Color(image.getRGB(verticalEdge ? m:arr[n], verticalEdge ? arr[n]:m));
red = c.getRed();
green = c.getGreen();
blue = c.getBlue();
//determine if the point is considered "dark" or not.
//modify the range if you want to only include really dark spots.
//occasionally, though, the edge might be blurred out, and light gray helps
if(red<239 && green<239 && blue<239){
result[n] = m;
break;
}
//count forwards or backwards depending on reverse variable
if(reverse){
m--;
}else{
m++;
}
}
}
return result;
}
}
A similar such problem I've done in the past basically figured out the orientation of the form, re-aligned it, re-scaled it, and I was all set. You can use the Hough transform to to detect the angular offset of the image (ie: how much it is rotated), but you still need to detect the boundaries of the form. It also had to accommodate for the boundaries of the piece of paper itself.
This was a lucky break for me, because it basically showed a black and white image in the middle of a big black border.
Apply an aggressive, 5x5 median filter to remove some noise.
Convert from grayscale to black and white (rescale intensity values from [0,255] to [0,1]).
Calculate the Principal Component Analysis (ie: calculate the Eigenvectors of the covariance matrix for your image from the calculated Eigenvalues) (http://en.wikipedia.org/wiki/Principal_component_analysis#Derivation_of_PCA_using_the_covariance_method)
4) This gives you a basis vector. You simply use that to re-orient your image to a standard basis matrix (ie: [1,0],[0,1]).
Your image is now aligned beautifully. I did this for normalizing the orientation of MRI scans of entire human brains.
You also know that you have a massive black border around the actual image. You simply keep deleting rows from the top and bottom, and both sides of the image until they are all gone. You can temporarily apply a 7x7 median or mode filter to a copy of the image so far at this point. It helps rule out too much border remaining in the final image from thumbprints, dirt, etc.
I'm working with sprite art, and I need to generate a polygon (array of vertices) for a collision detector.
I have a getPixel(x, y) method I can use to get the color of a pixel. I don't need any fancy color detection or anything, just solid pixels and transparent pixels. Here's what I started before my brain started to melt:
boolean[] hasColor = new boolean[size];
for (int i = 0; i < size; i++) {
int row;
row = i % width;
if ((pixmap.getPixel(i, row) != 0) || (pixmap.getPixel(row, i) != -256)) {
hasColor[i] = true;
} else {
hasColor[i] = false;
}
}
That should keep track of what pixels are empty, and what aren't. But I don't know where I should go from here.
Is there an algorithm or something I can use to help? Can someone provide input?
What you have is raster artwork.
What you need is a vector outline.
Converting from vector to raster is easy, raster to vector, not so much.
Here is one possible workflow:
Convert your artwork into a black-and-white image (like your pixel color present/not-present matrix).
Use Adobe Illustrator's "Live Trace" feature to vectorize this image.
Export the outline polygon into a format that you can read back easily.
Use this as your input for the collision detection.
Here's another approach:
A) Assume that the outline looks like a hexagon, like this:
*****
* *
* *
* *
* *
* *
*****
B) Define "fit" as the goodness of an outline, calculated by checking what percentage of the pixels are inside the hexagon (does not have to be the regular-shaped figure shown above).
C) Change the positions of the vertices, until you find an optimum fit (or until you get tired).
Step (C) is, of course, the hardest one. Plus, if your sprite needs more vertices, you may need to start out with an octagon/n-gon instead.
I want to draw text on canvas of certain width using .drawtext
For example, the width of the text should always be 400px no matter what the input text is.
If input text is longer it will decrease the font size, if input text is shorter it will increase the font size accordingly.
Here's a much more efficient method:
/**
* Sets the text size for a Paint object so a given string of text will be a
* given width.
*
* #param paint
* the Paint to set the text size for
* #param desiredWidth
* the desired width
* #param text
* the text that should be that width
*/
private static void setTextSizeForWidth(Paint paint, float desiredWidth,
String text) {
// Pick a reasonably large value for the test. Larger values produce
// more accurate results, but may cause problems with hardware
// acceleration. But there are workarounds for that, too; refer to
// http://stackoverflow.com/questions/6253528/font-size-too-large-to-fit-in-cache
final float testTextSize = 48f;
// Get the bounds of the text, using our testTextSize.
paint.setTextSize(testTextSize);
Rect bounds = new Rect();
paint.getTextBounds(text, 0, text.length(), bounds);
// Calculate the desired size as a proportion of our testTextSize.
float desiredTextSize = testTextSize * desiredWidth / bounds.width();
// Set the paint for that size.
paint.setTextSize(desiredTextSize);
}
Then, all you need to do is setTextSizeForWidth(paint, 400, str); (400 being the example width in the question).
For even greater efficiency, you can make the Rect a static class member, saving it from being instantiated each time. However, this may introduce concurrency issues, and would arguably hinder code clarity.
Try this:
/**
* Retrieve the maximum text size to fit in a given width.
* #param str (String): Text to check for size.
* #param maxWidth (float): Maximum allowed width.
* #return (int): The desired text size.
*/
private int determineMaxTextSize(String str, float maxWidth)
{
int size = 0;
Paint paint = new Paint();
do {
paint.setTextSize(++ size);
} while(paint.measureText(str) < maxWidth);
return size;
} //End getMaxTextSize()
Michael Scheper's solution seems nice but it didn't work for me, I needed to get the largest text size that is possible to draw in my view but this approach depends on the first text size you set, Every time you set a different size you'll get different results that can not say it is the right answer in every situation.
So I tried another way:
private float calculateMaxTextSize(String text, Paint paint, int maxWidth, int maxHeight) {
if (text == null || paint == null) return 0;
Rect bound = new Rect();
float size = 1.0f;
float step= 1.0f;
while (true) {
paint.getTextBounds(text, 0, text.length(), bound);
if (bound.width() < maxWidth && bound.height() < maxHeight) {
size += step;
paint.setTextSize(size);
} else {
return size - step;
}
}
}
It's simple, I increase the text size until the text rect bound dimensions are close enough to maxWidth and maxHeight, to decrease the loop repeats just change step to a bigger value (accuracy vs speed), Maybe it's not the best way to achieve this but It works.