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Image Resizing Bilinear Interpolation and Nearest Neighbour

I am currently having problems coming up with an algorithm for re-scaling and image.
I currently want to implement both Bilinear interpolation and Nearest Neighbour. I understand how both of them work conceptually but, I can not seem to record it into code. That I am still stuck on Nearest Neighbour
I have wrote some pseudo-code for it below (based on what I know):
Resizing Images: Nearest Neighbour
Use a loop:for j=0 to Yb-1
for i=0 to Xb-1
for c=0 to 2
(floor) y=j*Ya/Yb
(floor) x=i*Xa/Xb
Ib[j][i][c] = Ia[y][x][c]
My original data set (where I get my volume of data) is stored in a 3D array with [x][y][z] with (x, y, z).I read each pixel separately and can calculate the colors for each pixel using Color.color in java. I however, need to know how I can get the color (c = [0,1,2] ) for each pixel position x and y (x,y) excluding z(for one view's) to convert 1 old pixel for each new pixel into my new data set containing the new width and Height. I have written most of the code I have translated above in Java. But I still can not understand how to finalise a working implementation.
Thanks in Advance😊

I am not very familiar with java. But here is a working code for python.
import cv2
import numpy as np
img = cv2.imread("image.png")
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
scaleX = 0.5
scaleY = 0.5
newImg = np.zeros((int(img.shape[0]*scaleX),int(img.shape[1]*scaleY))).astype(np.uint8)
for y in range(newImg.shape[0]):
for x in range(newImg.shape[1]):
samplex = x/scaleX
sampley = y/scaleY
dx = samplex - np.floor(samplex)
dy = sampley - np.floor(sampley)
val = img[int(sampley-dy),int(samplex-dx)]*(1-dx)*(1-dy)
val += img[int(sampley + 1 - dy),int(samplex-dx)]*(1-dx)*(dy)
val += img[int(sampley-dy),int(samplex + 1 - dx)]*(dx)*(1-dy)
val += img[int(sampley + 1 -dy),int(samplex + 1 - dx)]*(dx)*(dy)
newImg[y,x] = val.astype(np.uint8)
cv2.imshow("img",newImg)
cv2.waitKey(0)
You could simply add one more for loop inside they for and x for loops to account for channels.

if I get it right you are interpolating volumes (voxels) instead of pixels in such case:
Lets have source volume vol1[xs1][ys1][zs1] and target vol0[xs0][ys0][zs0] where xs,ys,zs are the resolutions then nearest neighbor would be:
// vol0 <- vol1
for ( x0=0; x0<xs0; x0++)
for (x1=(x*x1)/x0, y0=0; y0<ys0; y0++)
for (y1=(y*y1)/y0, z0=0; z0<zs0; z0++)
{ z1=(z*z1)/z0;
vol0[x0][y0][z0]=vol1[x1][y1][z1];
}
The color stays the same for nearest neighbor. In case vol0 has smaller resolutions than vol1 you can do the for loops at vol1 resolution and compute x0,y0,z0 from x1,y1,z1 instead to speed up. Btw. all the variables are integers no floats needed for this...
Now for the color encoding in case your voxels are 1D array ({r,g,b}) instead of scalar integral type:
vol0[xs0][ys0][zs0][3]
vol1[xs1][ys1][zs1][3]
the stuff would change to:
// vol0 <- vol1
for ( x0=0; x0<xs0; x0++)
for (x1=(x*x1)/x0, y0=0; y0<ys0; y0++)
for (y1=(y*y1)/y0, z0=0; z0<zs0; z0++)
for (z1=(z*z1)/z0; i=0; i<3; i++ )
vol0[x0][y0][z0][i]=vol1[x1][y1][z1][i];

Render multiple heights in an isometric tile based map

Good evening everyone.
I've been messing a bit with isometric tile worlds and I have a few doubts about rendering the elements on it.
When I build a single height map I render it first and then add the diferent elements on top, and the displacement of the last seem right.
public void render(Graphics2D g2d) {
for(int i = 0; i < tileGrid.length; i++) {
Point isop = NeoMath.getInstance().cartToIso(i % yAmmount, i / yAmmount, GlobalDataStorage.tileWidth, GlobalDataStorage.tileHeight);
TileManager.getInstance().getTileByID(tileGrid[i]).render(g2d, isop.x, isop.y);
}
for(Entity entity : entityList) {
entity.render(g2d);
}
}
(The position of the entity is calculated inside it's update).
With this I have no problems as everything is rendered on the same height, the problem comes when I try to add other floors to it.
Let's say that I want it to have three heights. I have a list of list of tiles instead of the single array, and render every element on them:
public void render(Graphics2D g2d) {
int flag = 0;
for(int i = 0; i < tileGrid.size(); i++) {
Point isop = NeoMath.getInstance().cartToIso(i % yAmmount, i / yAmmount, GlobalDataStorage.tileWidth, GlobalDataStorage.tileHeight);
for(int k = 0; k < tileGrid.get(i).size(); k++) {
TileManager.getInstance().getTileByID(tileGrid.get(i).get(k)).render(g2d, isop.x, isop.y - (GlobalDataStorage.tileZ * k));
}
while(flag < currentList.size() &&
currentList.get(flag).getPosition().equals(new Point(i % yAmmount, i /
yAmmount))) {
currentList.get(flag).render(g2d);
flag++;
}
}
}
Where the currentList is the list of entities.
With this I have the problem that, when the entities move to a new position, they get overlaped by the tiles, as these are rendered after the entity, and the position of the entity does not change until it reached the destiny. I could change the position to the new one before rendering, but that implies that in the other axis the previous tile get rendered after the entity, making it disapear for a second due to the overlap.
This also mess when I try to draw selection rectangle as it get stuck behind the tiles being rendered. I don't want them to overlap the whole map so can't draw them after all the rendering has been done either.
Does someone know of another approach that I can try out?
Thank you beforehand.

Draw your entire floor layer in a first pass. Then in the second pass draw all walls and objects and moving entities.
I could change the position to the new one before rendering,
David Brevik, programmer on Diablo, mentions using this option in his GDC talk Diablo: A Classic Games Postmortem. It was his first "What Went Wrong" example!
Reference: https://www.youtube.com/watch?v=VscdPA6sUkc&t=20m17s
Turns out this is a classic hurdle in isometric games.

Image Processing Edge Detection in Java

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.

Slick is getting very slow but only drawin rectangles

I am using slick for java since a few days and got a serious problem.
If i run a completely empty apllication (it just shows the fps) with a solution of 800x600 i get a fps count between 700 and 800.
If I now draw an array with 13300 entries as a grid of green and white rectangles, the fps drop to something around 70.
With more entries in the array it becomes really slow.
For example in a solution of 1024x768 and an array with 21760 entries the fps drop to 40.
How i draw a single entry:
public void draw(Graphics graphics){
graphics.setColor(new Color(getColor().getRed(), getColor().getGreen(), getColor().getBlue(), getColor().getAlpha()));
graphics.fillRect(getPosition().x, getPosition().y, getSize().x, getSize().y);
Color_ARGB white = new Color_ARGB(Color_ARGB.ColorNames.WHITE);
graphics.setColor(new Color(white.getRed(), white.getGreen(), white.getBlue(), white.getAlpha()));
}
And this is how I draw the complete array:
public void draw(Graphics graphics) {
for (int ix = 0; ix < getWidth(); ix++) {
for (int iy = 0; iy < getHeight(); iy++) {
getGameGridAt(ix, iy).draw(graphics);
}
}
}
In my opinion 21760 is not that much.
Is there anything wrong with my code or is slick just too slow to draw so much rectangles?

You only want to draw rectangles that are on the screen. If your screen bounds go from 0 to 1024 in the x direction and from 0 to 768 in the y direction, then you only want to loop through rectangles that are inside those bounds and then only draw those rectangles. I can't imagine you are trying to draw 21760 rectangles inside those bounds.
If you are, then try creating one static rectangle and then just try drawing that ONE in all of the different positions you need to draw it at rather than creating a new one every time. For example, in a game I am making, I might have 1000 tiles that are "grass" tiles, but all 1000 of those share the same static texture. So I only need to reference one image rather than each tile creating its own.
Each rectangle can still have a unique state. Just make your own rectangle class and have a static final Image that holds a 5*5 image. Each rectangle will use this image when it needs to be drawn. You can still have unique properties for each rectangle. For example, private Vector2f position, private boolean isAlive, etc

You're probably not going to be able to draw individual rectangles any faster than that.
Games that render millions of polygons per second do so using vertex buffer objects (VBO). For that, you'll probably need to code against the OpenGL API (LWJGL) itself, not a wrapper.

Not sure if Slick will allow it, but if this thing looks anything like a chessboard grid... you could draw just 4 rectangles, grab them and use the resulting image as a texture for your whole image. I'm not even a java programmer just trying to come up with a solution.

Since you're only repeatedly using just a few colors creating a new Color object for every single one is bound to be slow... use new only once for each different color used and store the re-usable colors somewhere in your class, than call the functions with those, constantly allocating and freeing memory is very slow.
And while this might not be as much a benefit as not using new each time but have you considered caching the results of all those function calls and rewriting code as
public void draw(Graphics graphics) {
int ixmax = getWidth();
int iymax = getHeight();
for (int ix = 0; ix < ixmax; ix++) {
for (int iy = 0; iy < iymax; iy++) {
getGameGridAt(ix, iy).draw(graphics);
}
}
}
Or if you'd prefer not to declare new variables
public void draw(Graphics graphics) {
for (int ix = getWidth() - 1; ix >= 0; ix--) {
for (int iy = getHeight() - 1; iy >= 0; iy--) {
getGameGridAt(ix, iy).draw(graphics);
}
}
}

Just noticed in another answer you have an integral size grid (5x5) ... in this case the fastest way to go about this would seem to be to draw each item a single pixel (you can do this directly in memory using a 2-dimensional array) and scale it to 500% or use it as a texture and draw a single rectangle with it the final size you desire ... should be quite fast. Sorry for all the confusion caused by previous answers, you should have said what you're doing more clearly from the start.
If scaling and textures are not available you can still draw in memory using something like this (written in c++, please translate it to java yourself)
for( int x = 0; x < grid.width(); x++ ) {
for( int y = 0; y < grid.height(); y++ ) {
image[x*5][y*5] = grid.color[x][y];
image[x*5][y*5 + 1] = grid.color[x][y];
image[x*5][y*5 + 2] = grid.color[x][y];
image[x*5][y*5 + 3] = grid.color[x][y];
image[x*5][y*5 + 4] = grid.color[x][y];
}
memcpy(image[x*5+1], image[x*5], grid.height() * sizeof(image[0][0]) );
memcpy(image[x*5+2], image[x*5], grid.height() * sizeof(image[0][0]) );
memcpy(image[x*5+3], image[x*5], grid.height() * sizeof(image[0][0]) );
memcpy(image[x*5+4], image[x*5], grid.height() * sizeof(image[0][0]) );
}
I'm not sure, but perhaps for graphics the x and y might be represented in the reversed order than used here, so change the code accordingly if it that's the case (you'll figure that out as soon as a few iterations run), also your data is probably structured a bit differently but I think the idea should be clear.

How to dynamically construct 3d object by adding paths? (Java; OpenGL)

So I have some path generator which now works like this
http://www.openprocessing.org/visuals/?visualID=2615 (There is source; WQRNING - JAVA APPLET)
I want to create some 3D object using paths I generated so it locked in one of perspectives similar to what I get now in 2D.
So how do I dynamically construct 3D object by adding paths?
BTW: actually I ment algorithm like this http://www.derschmale.com/2009/07/20/slice-based-volume-rendering-using-pixel-bender/
So I want to create from such PATH (I do not want to use images and I do not want to use flash I want to use Java + OpenGl)
such 3d image (But note I want openGL Java and Path's))

I'm not sure I understand what you're after.
The example you supplied draws 2d paths, but merely uses z. scaling would have worked
in a similar way.
So How to dinamicly construct 3d
object by adding path's ?
Do you mean extruding/lathing an object, or replicating the scrunch sketch ?
Drawing a path is easy in processing, you just place vertex objects, in a for loop
between beginShape() and endShape() calls.
Here is the bit of code that does that in the example you've sent:
beginShape();
for (int p=0; p<pcount; p++){
vertex(Ring[p].position().x(),Ring[p].position().y());
}
endShape(CLOSE);
you can also call vertex(x,y,z)
I wanted to extrude a path a while back, here is my question in case it helps.
Basic sketch is uploaded here.
EDIT:
If you have an array of 2 polygons, you can just loop through them, and draw
using something similar to beginShape() and endShape(), GL_POLYGON might be handy.
e.g.
import processing.opengl.*;
import javax.media.opengl.*;
int zSpacing = 10;
PVector[][] slices;
void setup() {
size(600, 500, OPENGL);
slices = new PVector[3][3];
//dummy slice 1
slices[0][0] = new PVector(400, 200,-200);
slices[0][1] = new PVector(300, 400,-200);
slices[0][2] = new PVector(500, 400,-200);
//dummy slice 2
slices[1][0] = new PVector(410, 210,-200);
slices[1][1] = new PVector(310, 410,-200);
slices[1][2] = new PVector(510, 410,-200);
//dummy slice 3
slices[2][0] = new PVector(420, 220,-200);
slices[2][1] = new PVector(320, 420,-200);
slices[2][2] = new PVector(520, 420,-200);
}
void draw() {
background(255);
PGraphicsOpenGL pgl = (PGraphicsOpenGL) g; // g may change
GL gl = pgl.beginGL(); // always use the GL object returned by beginGL
for(int i = 0 ; i < slices.length; i ++){
gl.glColor3f(0, .15 * i, 0);
gl.glBegin(GL.GL_POLYGON);
for(int j = 0; j < slices[i].length; j++){
gl.glVertex3f(slices[i][j].x, slices[i][j].y,slices[i][j].z + (zSpacing * i));
}
gl.glEnd();
}
pgl.endGL();
}
The idea is you loop through each slice, and for each slice your loop through all its points. Obviously slices and the number of 3d vectors inside each slice is up to your data. Speaking of which, where does your data come from ?
If slices is not what your after volTron could come in handy:
volTron http://dm.ncl.ac.uk/joescully/voltronlib/images/s2.jpg
HTH,
George