Develop Reference

Java Junit4 testing; protected methods

I'm working to test this chunk of code - it's a class called MazeBuilder. My problem is that most of the methods are protected, so I can't access them in the tests...
So my thought was that the test should just focus on Run(), so it accesses a lot of the other methods. But I'm concerned that it will be impossible to get any sort of cohesive testing done operating from just one method.
Additionally, what is the proper way to test the 2 constructors ( MazeBuilder() and MazeBuilder(boolean deterministic) )? As it stands, I'm just testing that the object formed is not null - i.e. that they're being built at all. Is there a more expansive way of testing a constructor that I'm unaware of?
package falstad;
public class MazeBuilder implements Runnable {
// Given input information:
protected int width, height ; // width and height of maze,
Maze maze; // reference to the maze that is constructed, results are returned by calling maze.newMaze(..)
private int rooms; // requested number of rooms in maze, a room is an area with no walls larger than a single cell
int expectedPartiters; // user given limit for partiters
// Produced output information to create the new maze
// root, cells, dists, startx, starty
protected int startx, starty ; // starting position inside maze for entity to search for exit
// conventional encoding of maze as a 2 dimensional integer array encapsulated in the Cells class
// a single integer entry can hold information on walls, borders/bounds
protected Cells cells; // the internal representation of a maze as a matrix of cells
protected Distance dists ; // distance matrix that stores how far each position is away from the exit positino
// class internal local variables
protected SingleRandom random ; // random number stream, used to make randomized decisions, e.g for direction to go
Thread buildThread; // computations are performed in own separated thread with this.run()
//int colchange; // randomly selected in run method of this thread, used as parameter to Segment class constructor
/**
* Constructor for a randomized maze generation
*/
public MazeBuilder(){
random = SingleRandom.getRandom();
}
/**
* Constructor with option to make maze generation deterministic or random
*/
public MazeBuilder(boolean deterministic){
if (true == deterministic)
{
System.out.println("Project 2: functionality to make maze generation deterministic not implemented yet! Fix this!");
// Control random number generation
// TODO: implement code that makes sure that if MazeBuilder.build is called for same skill level twice, same results
// HINT: check http://download.oracle.com/javase/6/docs/api/java/util/Random.html and file SingleRandom.java
}
random = SingleRandom.getRandom();
}
/**
* Provides the sign of a given integer number
* #param num
* #return -1 if num < 0, 0 if num == 0, 1 if num > 0
*/
static int getSign(int num) {
return (num < 0) ? -1 : (num > 0) ? 1 : 0;
}
/**
* This method generates a maze.
* It computes distances, determines a start and exit position that are as far apart as possible.
*/
protected void generate() {
// generate paths in cells such that there is one strongly connected component
// i.e. between any two cells in the maze there is a path to get from one to the other
// the search algorithm starts at some random point
generatePathways();
final int[] remote = dists.computeDistances(cells) ;
// identify cell with the greatest distance
final int[] pos = dists.getStartPosition();
startx = pos[0] ;
starty = pos[1] ;
// make exit position at true exit in the cells data structure
setExitPosition(remote[0], remote[1]);
}
/**
* This method generates pathways into the maze.
*
*/
protected void generatePathways() {
int[][] origdirs = new int[width][height] ;
int x = random.nextIntWithinInterval(0, width-1) ;
int y = 0;
final int firstx = x ;
final int firsty = y ;
int dir = 0;
int origdir = dir;
cells.setVisitedFlagToZero(x, y);
while (true) {
int dx = Constants.DIRS_X[dir];
int dy = Constants.DIRS_Y[dir];
if (!cells.canGo(x, y, dx, dy)) {
dir = (dir+1) & 3;
if (origdir == dir) {
if (x == firstx && y == firsty)
break;
int odr = origdirs[x][y];
dx = Constants.DIRS_X[odr];
dy = Constants.DIRS_Y[odr];
x -= dx;
y -= dy;
origdir = dir = random.nextIntWithinInterval(0, 3);
}
} else {
cells.deleteWall(x, y, dx, dy);
x += dx;
y += dy;
cells.setVisitedFlagToZero(x, y);
origdirs[x][y] = dir;
origdir = dir = random.nextIntWithinInterval(0, 3);
}
}
}
/**
* Establish valid exit position by breaking down wall to outside area.
* #param remotex
* #param remotey
*/
protected void setExitPosition(int remotex, int remotey) {
int bit = 0;
if (remotex == 0)
bit = Constants.CW_LEFT;
else if (remotex == width-1)
bit = Constants.CW_RIGHT;
else if (remotey == 0)
bit = Constants.CW_TOP;
else if (remotey == height-1)
bit = Constants.CW_BOT;
else
dbg("Generate 1");
cells.setBitToZero(remotex, remotey, bit);
//System.out.println("exit position set to zero: " + remotex + " " + remotey + " " + bit + ":" + cells.hasMaskedBitsFalse(remotex, remotey, bit)
// + ", Corner case: " + ((0 == remotex && 0 == remotey) || (0 == remotex && height-1 == remotey) || (width-1 == remotex && 0 == remotey) || (width-1 == remotex && height-1 == remotey)));
}
static final int MIN_ROOM_DIMENSION = 3 ;
static final int MAX_ROOM_DIMENSION = 8 ;
/**
* Allocates space for a room of random dimensions in the maze.
* The position of the room is chosen randomly. The method is not sophisticated
* such that the attempt may fail even if the maze has ample space to accommodate
* a room of the chosen size.
* #return true if room is successfully placed, false otherwise
*/
private boolean placeRoom() {
// get width and height of random size that are not too large
// if too large return as a failed attempt
final int rw = random.nextIntWithinInterval(MIN_ROOM_DIMENSION, MAX_ROOM_DIMENSION);
if (rw >= width-4)
return false;
final int rh = random.nextIntWithinInterval(MIN_ROOM_DIMENSION, MAX_ROOM_DIMENSION);
if (rh >= height-4)
return false;
// proceed for a given width and height
// obtain a random position (rx,ry) such that room is located on as a rectangle with (rx,ry) and (rxl,ryl) as corner points
// upper bound is chosen such that width and height of room fits maze area.
final int rx = random.nextIntWithinInterval(1, width-rw-1);
final int ry = random.nextIntWithinInterval(1, height-rh-1);
final int rxl = rx+rw-1;
final int ryl = ry+rh-1;
// check all cells in this area if they already belong to a room
// if this is the case, return false for a failed attempt
if (cells.areaOverlapsWithRoom(rx, ry, rxl, ryl))
return false ;
// since the area is available, mark it for this room and remove all walls
// from this on it is clear that we can place the room on the maze
cells.markAreaAsRoom(rw, rh, rx, ry, rxl, ryl);
return true;
}
static void dbg(String str) {
System.out.println("MazeBuilder: "+str);
}
/**
* Fill the given maze object with a newly computed maze according to parameter settings
* #param mz maze to be filled
* #param w width of requested maze
* #param h height of requested maze
* #param roomct number of rooms
* #param pc number of expected partiters
*/
public void build(Maze mz, int w, int h, int roomct, int pc) {
init(mz, w, h, roomct, pc);
buildThread = new Thread(this);
buildThread.start();
}
/**
* Initialize internal attributes, method is called by build() when input parameters are provided
* #param mz maze to be filled
* #param w width of requested maze
* #param h height of requested maze
* #param roomct number of rooms
* #param pc number of expected partiters
*/
private void init(Maze mz, int w, int h, int roomct, int pc) {
// store parameters
maze = mz;
width = w;
height = h;
rooms = roomct;
expectedPartiters = pc;
// initialize data structures
cells = new Cells(w,h) ;
dists = new Distance(w,h) ;
//colchange = random.nextIntWithinInterval(0, 255); // used in the constructor for Segments class Seg
}
static final long SLEEP_INTERVAL = 100 ; //unit is millisecond
/**
* Main method to run construction of a new maze with a MazeBuilder in a thread of its own.
* This method is called internally by the build method when it sets up and starts a new thread for this object.
*/
public void run() {
// try-catch block to recognize if thread is interrupted
try {
// create an initial invalid maze where all walls and borders are up
cells.initialize();
// place rooms in maze
generateRooms();
Thread.sleep(SLEEP_INTERVAL) ; // test if thread has been interrupted, i.e. notified to stop
// put pathways into the maze, determine its starting and end position and calculate distances
generate();
Thread.sleep(SLEEP_INTERVAL) ; // test if thread has been interrupted, i.e. notified to stop
final int colchange = random.nextIntWithinInterval(0, 255); // used in the constructor for Segments class Seg
final BSPBuilder b = new BSPBuilder(maze, dists, cells, width, height, colchange, expectedPartiters) ;
BSPNode root = b.generateBSPNodes();
Thread.sleep(SLEEP_INTERVAL) ; // test if thread has been interrupted, i.e. notified to stop
// dbg("partiters = "+partiters);
// communicate results back to maze object
maze.newMaze(root, cells, dists, startx, starty);
}
catch (InterruptedException ex) {
// necessary to catch exception to avoid escalation
// exception mechanism basically used to exit method in a controlled way
// no need to clean up internal data structures
// dbg("Catching signal to stop") ;
}
}
static final int MAX_TRIES = 250 ;
/**
* Generate all rooms in a given maze where initially all walls are up. Rooms are placed randomly and of random sizes
* such that the maze can turn out to be too small to accommodate the requested number of rooms (class attribute rooms).
* In that case less rooms are produced.
* #return generated number of rooms
*/
private int generateRooms() {
// Rooms are randomly positioned such that it may be impossible to place the all rooms if the maze is too small
// to prevent an infinite loop we limit the number of failed to MAX_TRIES == 250
int tries = 0 ;
int result = 0 ;
while (tries < MAX_TRIES && result <= rooms) {
if (placeRoom())
result++ ;
else
tries++ ;
}
return result ;
}
/**
* Notify the maze builder thread to stop the creation of a maze and to terminate
*/
public void interrupt() {
buildThread.interrupt() ;
}
}

To unit test your protected methods, simply put your test class in the same package as the class you are looking to test (in this case falsted). Just because they are in the same package, it doesn't mean they have to be in the same directory (just a parallel test directory hierarchy).
For example, if you are using maven, your source would be in src/main/java/falsted and your tests would be in src/test/java/falsted. From a maven perspective, these are separate directories and therefore can easily be managed separately, while from a Java perspective, they are the same package (so protected methods are visible).
Test your constructors by probing the state of the object to ensure that all values got their default or initial value.

You can use protected in test method. Recommended way to structure your project is.
In src/main/java
package falstad;
public class MazeBuilder {}
In src/test/java
package falstad;
public class MazeBuilderTest {}

Detecting closest element in array

I'm having issues detecting the closest element in an array of blocks to the player (using circles).
What I have so far is:
public static int closestBarrier(GameObject object, GameObject[] barriers) {
int closest = -1;
float minDistSq = Float.MAX_VALUE;// ridiculously large value to start
for (int i = 0; i < barriers.length; i++) {
float barrierRadius = barriers[i].getWidth() / 2;
float objectRadius = object.getWidth() / 2;
GameObject curr = barriers[i];// current
float dx = (object.getX()) - ((curr.getX()));
float dy = (object.getY()) - ((curr.getY()));
float distSq = (((dx * dx + dy * dy) - objectRadius) - barrierRadius) ;// use the squared distance
if (distSq < minDistSq) {// find the smallest and remember the id
minDistSq = distSq;
closest = i;
}
}
return closest;
}
It passes most of the tests but on the final one the returned index of the closest one is 2 instead of the expected 3. Here are the tests (it is failing 'closest to fourth' :
public final void testClosestBarrier() {
// Closest to first
GameObject player = new GameObject(0,1);
player.setWidth(2);
GameObject[] barriers = new GameObject[4];
barriers[0] = new GameObject(8,9);
barriers[0].setWidth(3);
barriers[1] = new GameObject(10,15);
barriers[1].setWidth(2);
barriers[2] = new GameObject(15,20);
barriers[2].setWidth(5);
barriers[3] = new GameObject(100,210);
barriers[3].setWidth(10);
assertEquals("Player closest to first barrier",0,
Submission.closestBarrier(player,barriers));
// Closest to second
player.setX(12);
player.setY(12);
assertEquals("Player closest to second barrier",1,
Submission.closestBarrier(player,barriers));
// Closest to third
player.setX(12);
player.setY(20);
assertEquals("Player closest to third barrier",2,
Submission.closestBarrier(player,barriers));
// Closest to fourth
player.setX(90);
player.setY(100);
assertEquals("Player closest to fourth barrier",3,
Submission.closestBarrier(player,barriers));
}

Your code is correct and the test you have written is wrong - barrier 2 is closer to 90,100 than barrier 3.
barrier 2:
(90-15)^2 + (100-20)^2
12025
barrier 3:
(100-90)^2 + (210-100)^2
12200
12025 < 12200 -> barrier 2 is closer
EDIT: In your edited answer, you forgot to square objectRadius and barrierRadius. e.g.
float distSq = (((dx * dx + dy * dy) - objectRadius) - barrierRadius)
In this line, you have dx^2, dy^2 but only non-squared objectRadius and barrierRadius.

Pixel level collision detection fails for small objects. (Java)

For a project we were given a game engine off which to create a game. We, as part of this, have to implement pixel level collision detection after a possible collision has been found via a bounding box detection method. I have implemented both but my pixel level test fails for small objects (bullets in this case). I have checked if it works for slow bullets but that fails too.
For my pixel level implementation I create bitmasks for each texture using an the available IntBuffer (a ByteBuffer is available too?). The IntBuffer is in RGBA format and its size is width*height, I placed this in a 2D array and replaced all non-zero numbers with 1's to create the mask. After a collision of bounding boxes I find the rectangle represented by the overlap (using .createIntersection) and then check the maps of both sprites within this intersection for a nonzero pixel from both using bitwise AND.
Here is my code for the pixel level test:
/**
* Pixel level test
*
* #param rect the rectangle representing the intersection of the bounding
* boxes
* #param index1 the index at which the first objects texture is stored
* #param index the index at which the second objects texture is stored
*/
public static boolean isBitCollision(Rectangle2D rect, int index1, int index2)
{
int height = (int) rect.getHeight();
int width = (int) rect.getWidth();
long mask1 = 0;
long mask2 = 0;
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
mask1 = mask1 + bitmaskArr[index1].bitmask[i][j];//add up the current column of "pixels"
mask2 = mask2 + bitmaskArr[index2].bitmask[i][j];
if (((mask1) & (mask2)) != 0)//bitwise and, if both are nonzero there is a collsion
{
return true;
}
mask1 = 0;
mask2 = 0;
}
}
return false;
}
I've been struggling with this for days and any help will be greatly appreciated.

I managed to solve my own issue and now it works properly. For anyone interested what I did was find the rectangle created by the overlap of the two bounding boxes of the two sprites. I then dropped each object to the origin along with it, relatively, the rectangle of intersection. It should be noted that I dropped each object to a "separate" origin - ie I effectively had two rectangle of intersection afterwards - one for each. The co-ordinates of each rectangle of intersection, now in bounds of the bitmask 2D arrays for both objects, were used to check the correct regions for overlap of both objects:
I loop bottom to top left to right through the bitmask as the image data provided in upside - apparently this is the norm for image data.
/**
* My Pixel level test - 2D
*
* #param rect the rectangle representing the intersection of the bounding
* boxes
* #param index1 the index at which the first objects texture is stored
* #param index2 the index at which the second objects texture is stored
* #param p1 the position of object 1
* #param p2 the position of object 2
* #return true if there is a collision at a pixel level false if not
*/
//public static boolean isPixelCollision(Rectangle2D rect, Point2D.Float p1, Bitmask bm1, Point2D.Float p2, Bitmask bm2)
public static boolean isPixelCollision(Rectangle2D rect, Point2D.Float p1, int index1, Point2D.Float p2, int index2)
{
int height = (int) rect.getHeight();
int width = (int) rect.getWidth();
byte mask1 = 0;
byte mask2 = 0;
//drop both objects to the origin and drop a rectangle of intersection for each along with them
//this allows for us to have the co-ords of the rect on intersection within them at number that are inbounds.
Point2D.Float origP1 = new Point2D.Float((float) Math.abs(rect.getX() - p1.x), (float) Math.abs(rect.getY() - p1.y));//rect for object one
Point2D.Float origP2 = new Point2D.Float((float) Math.abs(rect.getX() - p2.x), (float) Math.abs(rect.getY() - p2.y));//rect for object two
//to avoid casting with every iteration
int start1y = (int) origP1.y;
int start1x = (int) origP1.x;
int start2y = (int) origP2.y;
int start2x = (int) origP2.x;
//we need to loop within the rect of intersection
//goind bottom up and left to right
for (int i = height - 1; i > 0; i--)
{
for (int j = 0; j < width; j++)
{
mask1 = bitmaskArr[index1].bitmask[start1y + i][start1x + j];
mask2 = bitmaskArr[index2].bitmask[start2y + i][start2x + j];
if ((mask1 & mask2) > 0)
{
return true;
}
}
}
//no collsion was found
return false;
}

The problem could be with this part of the code:
if (((mask1) & (mask2)) != 0)//bitwise and, if both are nonzero there is a collsion
{
return true;
}
you seem to be using a bitwise and for checking whether both values are non zero - but this may not work in such a manner.
For instance the value of the following expression:
3 & 4 == 0
is true
This is because when you do a bitwise operation you need to think of the numbers as their bit representation and do the operation bit-by-bit.
So:
3 = 0000 0011
& 4 = 0000 0100
---------------
0 = 0000 0000
this is because of how the 1 bit values align to one another. For a bit in a bitwise and to have the value of 1 - two bits at the same location in the different numbers need to be 1.
Another example would be:
3 = 0000 0011
& 2 = 0000 0010
---------------
2 = 0000 0010
So in your case a better check would be:
if ( mask1>0 && mask2>0 )//logical and if both are nonzero there is a collsion
{
return true;
}

Image interpolation - nearest neighbor (Processing)

I've been having trouble with an image interpolation method in Processing. This is the code I've come up with and I'm aware that it will throw an out of bounds exception since the outer loop goes further than the original image but how can I fix that?
PImage nearestneighbor (PImage o, float sf)
{
PImage out = createImage((int)(sf*o.width),(int)(sf*o.height),RGB);
o.loadPixels();
out.loadPixels();
for (int i = 0; i < sf*o.height; i++)
{
for (int j = 0; j < sf*o.width; j++)
{
int y = round((o.width*i)/sf);
int x = round(j / sf);
out.pixels[(int)((sf*o.width*i)+j)] = o.pixels[(y+x)];
}
}
out.updatePixels();
return out;
}
My idea was to divide both components that represent the point in the scaled image by the scale factor and round it in order to obtain the nearest neighbor.

For getting rid of the IndexOutOfBoundsException try caching the result of (int)(sf*o.width) and (int)(sf*o.height).
Additionally you might want to make sure that x and y don't leave the bounds, e.g. by using Math.min(...) and Math.max(...).
Finally, it should be int y = round((i / sf) * o.width; since you want to get the pixel in the original scale and then muliply with the original width. Example: Assume a 100x100 image and a scaling factor of 1.2. The scaled height would be 120 and thus the highest value for i would be 119. Now, round((119 * 100) / 1.2) yields round(9916.66) = 9917. On the other hand round(119 / 1.2) * 100 yields round(99.16) * 100 = 9900 - you have a 17 pixel difference here.
Btw, the variable name y might be misleading here, since its not the y coordinate but the index of the pixel at the coordinates (0,y), i.e. the first pixel at height y.
Thus your code might look like this:
int scaledWidth = (int)(sf*o.width);
int scaledHeight = (int)(sf*o.height);
PImage out = createImage(scaledWidth, scaledHeight, RGB);
o.loadPixels();
out.loadPixels();
for (int i = 0; i < scaledHeight; i++) {
for (int j = 0; j < scaledWidth; j++) {
int y = Math.min( round(i / sf), o.height ) * o.width;
int x = Math.min( round(j / sf), o.width );
out.pixels[(int)((scaledWidth * i) + j)] = o.pixels[(y + x)];
}
}

Java image analysis - counting vertical lines

I need a little help on an image analysis algorithm in Java. I basically have images like this:
So, as you might guessed, I need to count the lines.
What approach do you think would be best?
Thanks,
Smaug

A simple segmentation algorithm can help you out. Heres how the algorithm works:
scan pixels from left to right and
record the position of the first
black (whatever the color of your
line is) pixel.
carry on this process
unless you find one whole scan when
you don't find the black pixel.
Record this position as well.
We are
just interested in the Y positions
here. Now using this Y position
segment the image horizontally.
Now
we are going to do the same process
but this time we are going to scan
from top to bottom (one column at a
time) in the segment we just created.
This time we are interested in X
positions.
So in the end we get every
lines extents or you can say a
bounding box for every line.
The
total count of these bounding boxes
is the number of lines.
You can do many optimizations in the algorithm according to your needs.

package ac.essex.ooechs.imaging.commons.edge.hough;
import java.awt.image.BufferedImage;
import java.awt.*;
import java.util.Vector;
import java.io.File;
/**
* <p/>
* Java Implementation of the Hough Transform.<br />
* Used for finding straight lines in an image.<br />
* by Olly Oechsle
* </p>
* <p/>
* Note: This class is based on original code from:<br />
* http://homepages.inf.ed.ac.uk/rbf/HIPR2/hough.htm
* </p>
* <p/>
* If you represent a line as:<br />
* x cos(theta) + y sin (theta) = r
* </p>
* <p/>
* ... and you know values of x and y, you can calculate all the values of r by going through
* all the possible values of theta. If you plot the values of r on a graph for every value of
* theta you get a sinusoidal curve. This is the Hough transformation.
* </p>
* <p/>
* The hough tranform works by looking at a number of such x,y coordinates, which are usually
* found by some kind of edge detection. Each of these coordinates is transformed into
* an r, theta curve. This curve is discretised so we actually only look at a certain discrete
* number of theta values. "Accumulator" cells in a hough array along this curve are incremented
* for X and Y coordinate.
* </p>
* <p/>
* The accumulator space is plotted rectangularly with theta on one axis and r on the other.
* Each point in the array represents an (r, theta) value which can be used to represent a line
* using the formula above.
* </p>
* <p/>
* Once all the points have been added should be full of curves. The algorithm then searches for
* local peaks in the array. The higher the peak the more values of x and y crossed along that curve,
* so high peaks give good indications of a line.
* </p>
*
* #author Olly Oechsle, University of Essex
*/
public class HoughTransform extends Thread {
public static void main(String[] args) throws Exception {
String filename = "/home/ooechs/Desktop/vase.png";
// load the file using Java's imageIO library
BufferedImage image = javax.imageio.ImageIO.read(new File(filename));
// create a hough transform object with the right dimensions
HoughTransform h = new HoughTransform(image.getWidth(), image.getHeight());
// add the points from the image (or call the addPoint method separately if your points are not in an image
h.addPoints(image);
// get the lines out
Vector<HoughLine> lines = h.getLines(30);
// draw the lines back onto the image
for (int j = 0; j < lines.size(); j++) {
HoughLine line = lines.elementAt(j);
line.draw(image, Color.RED.getRGB());
}
}
// The size of the neighbourhood in which to search for other local maxima
final int neighbourhoodSize = 4;
// How many discrete values of theta shall we check?
final int maxTheta = 180;
// Using maxTheta, work out the step
final double thetaStep = Math.PI / maxTheta;
// the width and height of the image
protected int width, height;
// the hough array
protected int[][] houghArray;
// the coordinates of the centre of the image
protected float centerX, centerY;
// the height of the hough array
protected int houghHeight;
// double the hough height (allows for negative numbers)
protected int doubleHeight;
// the number of points that have been added
protected int numPoints;
// cache of values of sin and cos for different theta values. Has a significant performance improvement.
private double[] sinCache;
private double[] cosCache;
/**
* Initialises the hough transform. The dimensions of the input image are needed
* in order to initialise the hough array.
*
* #param width The width of the input image
* #param height The height of the input image
*/
public HoughTransform(int width, int height) {
this.width = width;
this.height = height;
initialise();
}
/**
* Initialises the hough array. Called by the constructor so you don't need to call it
* yourself, however you can use it to reset the transform if you want to plug in another
* image (although that image must have the same width and height)
*/
public void initialise() {
// Calculate the maximum height the hough array needs to have
houghHeight = (int) (Math.sqrt(2) * Math.max(height, width)) / 2;
// Double the height of the hough array to cope with negative r values
doubleHeight = 2 * houghHeight;
// Create the hough array
houghArray = new int[maxTheta][doubleHeight];
// Find edge points and vote in array
centerX = width / 2;
centerY = height / 2;
// Count how many points there are
numPoints = 0;
// cache the values of sin and cos for faster processing
sinCache = new double[maxTheta];
cosCache = sinCache.clone();
for (int t = 0; t < maxTheta; t++) {
double realTheta = t * thetaStep;
sinCache[t] = Math.sin(realTheta);
cosCache[t] = Math.cos(realTheta);
}
}
/**
* Adds points from an image. The image is assumed to be greyscale black and white, so all pixels that are
* not black are counted as edges. The image should have the same dimensions as the one passed to the constructor.
*/
public void addPoints(BufferedImage image) {
// Now find edge points and update the hough array
for (int x = 0; x < image.getWidth(); x++) {
for (int y = 0; y < image.getHeight(); y++) {
// Find non-black pixels
if ((image.getRGB(x, y) & 0x000000ff) != 0) {
addPoint(x, y);
}
}
}
}
/**
* Adds a single point to the hough transform. You can use this method directly
* if your data isn't represented as a buffered image.
*/
public void addPoint(int x, int y) {
// Go through each value of theta
for (int t = 0; t < maxTheta; t++) {
//Work out the r values for each theta step
int r = (int) (((x - centerX) * cosCache[t]) + ((y - centerY) * sinCache[t]));
// this copes with negative values of r
r += houghHeight;
if (r < 0 || r >= doubleHeight) continue;
// Increment the hough array
houghArray[t][r]++;
}
numPoints++;
}
/**
* Once points have been added in some way this method extracts the lines and returns them as a Vector
* of HoughLine objects, which can be used to draw on the
*
* #param percentageThreshold The percentage threshold above which lines are determined from the hough array
*/
public Vector<HoughLine> getLines(int threshold) {
// Initialise the vector of lines that we'll return
Vector<HoughLine> lines = new Vector<HoughLine>(20);
// Only proceed if the hough array is not empty
if (numPoints == 0) return lines;
// Search for local peaks above threshold to draw
for (int t = 0; t < maxTheta; t++) {
loop:
for (int r = neighbourhoodSize; r < doubleHeight - neighbourhoodSize; r++) {
// Only consider points above threshold
if (houghArray[t][r] > threshold) {
int peak = houghArray[t][r];
// Check that this peak is indeed the local maxima
for (int dx = -neighbourhoodSize; dx <= neighbourhoodSize; dx++) {
for (int dy = -neighbourhoodSize; dy <= neighbourhoodSize; dy++) {
int dt = t + dx;
int dr = r + dy;
if (dt < 0) dt = dt + maxTheta;
else if (dt >= maxTheta) dt = dt - maxTheta;
if (houghArray[dt][dr] > peak) {
// found a bigger point nearby, skip
continue loop;
}
}
}
// calculate the true value of theta
double theta = t * thetaStep;
// add the line to the vector
lines.add(new HoughLine(theta, r));
}
}
}
return lines;
}
/**
* Gets the highest value in the hough array
*/
public int getHighestValue() {
int max = 0;
for (int t = 0; t < maxTheta; t++) {
for (int r = 0; r < doubleHeight; r++) {
if (houghArray[t][r] > max) {
max = houghArray[t][r];
}
}
}
return max;
}
/**
* Gets the hough array as an image, in case you want to have a look at it.
*/
public BufferedImage getHoughArrayImage() {
int max = getHighestValue();
BufferedImage image = new BufferedImage(maxTheta, doubleHeight, BufferedImage.TYPE_INT_ARGB);
for (int t = 0; t < maxTheta; t++) {
for (int r = 0; r < doubleHeight; r++) {
double value = 255 * ((double) houghArray[t][r]) / max;
int v = 255 - (int) value;
int c = new Color(v, v, v).getRGB();
image.setRGB(t, r, c);
}
}
return image;
}
}
Source: http://vase.essex.ac.uk/software/HoughTransform/HoughTransform.java.html

I've implemented a simple solution (must be improved) using Marvin Framework that finds the vertical lines start and end points and prints the total number of lines found.
Approach:
Binarize the image using a given threshold.
For each pixel, if it is black (solid), try to find a vertical line
Save the x,y, of the start and end points
The line has a minimum lenght? It is an acceptable line!
Print the start point in red and the end point in green.
The output image is shown below:
The programs output:
Vertical line fount at: (74,9,70,33)
Vertical line fount at: (113,9,109,31)
Vertical line fount at: (80,10,76,32)
Vertical line fount at: (137,11,133,33)
Vertical line fount at: (163,11,159,33)
Vertical line fount at: (184,11,180,33)
Vertical line fount at: (203,11,199,33)
Vertical line fount at: (228,11,224,33)
Vertical line fount at: (248,11,244,33)
Vertical line fount at: (52,12,50,33)
Vertical line fount at: (145,13,141,35)
Vertical line fount at: (173,13,169,35)
Vertical line fount at: (211,13,207,35)
Vertical line fount at: (94,14,90,36)
Vertical line fount at: (238,14,236,35)
Vertical line fount at: (130,16,128,37)
Vertical line fount at: (195,16,193,37)
Vertical lines total: 17
Finally, the 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.MarvinPluginLoader;
public class VerticalLineCounter {
private MarvinImagePlugin threshold = MarvinPluginLoader.loadImagePlugin("org.marvinproject.image.color.thresholding");
public VerticalLineCounter(){
// Binarize
MarvinImage image = MarvinImageIO.loadImage("./res/lines.jpg");
MarvinImage binImage = image.clone();
threshold.setAttribute("threshold", 127);
threshold.process(image, binImage);
// Find lines and save an output image
MarvinImage imageOut = findVerticalLines(binImage, image);
MarvinImageIO.saveImage(imageOut, "./res/lines_out.png");
}
private MarvinImage findVerticalLines(MarvinImage binImage, MarvinImage originalImage){
MarvinImage imageOut = originalImage.clone();
boolean[][] processedPixels = new boolean[binImage.getWidth()][binImage.getHeight()];
int color;
Point endPoint;
int totalLines=0;
for(int y=0; y<binImage.getHeight(); y++){
for(int x=0; x<binImage.getWidth(); x++){
if(!processedPixels[x][y]){
color = binImage.getIntColor(x, y);
// Black?
if(color == 0xFF000000){
endPoint = getEndOfLine(x,y,binImage,processedPixels);
// Line lenght threshold
if(endPoint.x - x > 5 || endPoint.y - y > 5){
imageOut.fillRect(x-2, y-2, 5, 5, Color.red);
imageOut.fillRect(endPoint.x-2, endPoint.y-2, 5, 5, Color.green);
totalLines++;
System.out.println("Vertical line fount at: ("+x+","+y+","+endPoint.x+","+endPoint.y+")");
}
}
}
processedPixels[x][y] = true;
}
}
System.out.println("Vertical lines total: "+totalLines);
return imageOut;
}
private Point getEndOfLine(int x, int y, MarvinImage image, boolean[][] processedPixels){
int xC=x;
int cY=y;
while(true){
processedPixels[xC][cY] = true;
processedPixels[xC-1][cY] = true;
processedPixels[xC-2][cY] = true;
processedPixels[xC-3][cY] = true;
processedPixels[xC+1][cY] = true;
processedPixels[xC+2][cY] = true;
processedPixels[xC+3][cY] = true;
if(getSafeIntColor(xC,cY,image) < 0xFF000000){
// nothing
}
else if(getSafeIntColor(xC-1,cY,image) == 0xFF000000){
xC = xC-2;
}
else if(getSafeIntColor(xC-2,cY,image) == 0xFF000000){
xC = xC-3;
}
else if(getSafeIntColor(xC+1,cY,image) == 0xFF000000){
xC = xC+2;
}
else if(getSafeIntColor(xC+2,cY,image) == 0xFF000000){
xC = xC+3;
}
else{
return new Point(xC, cY);
}
cY++;
}
}
private int getSafeIntColor(int x, int y, MarvinImage image){
if(x >= 0 && x < image.getWidth() && y >= 0 && y < image.getHeight()){
return image.getIntColor(x, y);
}
return -1;
}
public static void main(String args[]){
new VerticalLineCounter();
System.exit(0);
}
}

It depends on how much they look like that.
Bring the image to 1-bit (black and white) in a way that preserves the lines and brings the background to pure white
Perhaps do simple cleanup like speck removal (remove any small black components).
Then,
Find a black pixel
Use flood-fill algorithms to find its extent
See if the shape meets the criteria for being a line (lineCount++ if so)
remove it
Repeat this until there are no black pixels
A lot depends on how good you do #3, some ideas
Use Hough just on this section to check that you have one line, and that it is vertical(ish)
(after #1) rotate it to the vertical and check its width/height ratio