i am new in image processing and computer vision and i would like to detect blobs in an image using Laplacian of Gaussian with different scale spaces. The following links explain in detail.
http://www.cs.utah.edu/~jfishbau/advimproc/project1/
http://www.cs.utah.edu/~manasi/coursework/cs7960/p1/project1.html
So far by using opencv2 i have managed to get the images, apply the Gaussian filter with various kernels and apply the Laplacian filter. The i multiply with sigma squared the whole image to amplify the signal (see description in links) and then i apply a threshhold. The next step is to detect local maxima and minima so i can get the blob center and be able to draw circles, but i am not sure how to do it and whether the image processing i have done so far is correct. Here is my code:
int main(){
image1 = imread("butterfly.jpg",0);
drawing1 = imread("butterfly.jpg");
blobDetect(image1,drawing1);
waitKey();
return 0;
}
void blobDetect(Mat image, Mat drawing){
int ksize = 1;
int n =1;
Mat result[10];
for(int i=0; i<10; i++){
cv::GaussianBlur(image,result[i],cv::Size(ksize,ksize),ksize/3,0);
n+=1;
ksize = 2*n-1;
}
ksize = 1;
n =1;
for(int i=0; i<10; i++){
cv::Laplacian(result[i],result[i],CV_8U,ksize,1,0);
n+=1;
ksize = 2*n-1;
}
ksize = 1;
int cols = image.cols;
int rows = image.rows;
for(int a=0; a<10; a++){
for(int i=0; i<rows; i++){
//uchar* data = result[a].ptr<uchar>(rows);
for(int j=0; j<cols; j++){
result[a].at<uchar>(i,j) *= (ksize/3)*(ksize/3);
}
}
ksize++;
ksize = 2*ksize-1;
}
for(int i=0; i<10; i++){
cv::threshold(result[i], result[i], 100, 255, 0);
}
}
This is the expected result
Thanks
After you detect contours, you can use
minEnclosingCircle()
Even better is to check out this tutorial:
http://docs.opencv.org/doc/tutorials/imgproc/shapedescriptors/bounding_rects_circles/bounding_rects_circles.html
Related
I am making a dice generator, which rolls 2 dices a thousand times and gives the output to an array, which is then displayed as bar charts on the graphic output. Now i want to add the dice numbers at the bottom of the chart (and also turn the chart around ), but it doesnt seem like i get any output [this line-> text(String.format("%s",i),i+w*(width/11),280,(width/11),280); ]. Did i place it in the wrong function, because the code should work like that( i ve adapted it from a previous project). [my dice has the numbers 0-5 on it just so i dont get that confused by the array starting at 0, im still fairly new to that]. Thank you in advance!
import java.util.Random;
Random rg = new Random();
final int N=1000;
void setup(){
println(f);
println(p);
size(700,500);
background(255);
}
int [] f=countDice2(N);
float[] p= getProbabilities(f);
int [] countDice2(int N){
int[] f = new int [11];
for(int i =0; i<N;i++){
int k =rg.nextInt(6);
int u= rg.nextInt(6);
int t =u+k;
f[t] +=1;
}
return f;
}
float[] getProbabilities(int[] f){
int n=0;
for(int j=0; j< f.length; j++){
n=n+f[j];
}
float[] prob=new float[f.length];
for(int i=0; i<f.length;i++){
prob[i]= (float)f[i]/n;
}
return prob;
}
void plotProbabilities(){
for( int i =0, w =0;w<=11 && i< 11; i++, w++){
//fill(0,255,0);
rect(i+w*(width/11) ,300,(width/11),f[0+i]);
}
}
void draw(){
plotProbabilities();
for( int i =0, w =0;w<=11 && i< 11; i++, w++){
text(String.format("%s",i),i+w*(width/11),280,(width/11),280);
}
}
Your mistake is very simple: you're writing in white.
Look how I found out:
void draw() {
plotProbabilities();
for ( int i =0, w =0; w<=11 && i< 11; i++, w++) {
fill(0);
text("" + i, i+w*(width/11), 280, (width/11), 280);
}
}
Think of fill() as changing pencil: everything you do after will use the new pencil, so the new color. If you draw several different things with their own color, you have to specify the fill color for every one.
You nailed it. This is just a small mistake.
Have fun!
I am trying to make an old TV static type effect in P5.js, and although I am able to make the effect work, the frame rate is quite low.
My approach is the following:
Loop through each pixel
Set the stroke to a random value
Call the point() function to paint the pixel
Initially, I was doing this in the draw function directly but it was very slow. I was getting less than 1 frame a second. So I switch to the following paint buffer approach:
const SCREEN_WIDTH = 480
const SCREEN_HEIGHT = 480
var ScreenBuffer;
function setup(){
createCanvas(SCREEN_WIDTH, SCREEN_HEIGHT);
ScreenBuffer = createGraphics(SCREEN_WIDTH,SCREEN_HEIGHT);
}
function draw(){
paintBuffer();
image(ScreenBuffer,0,0);
}
function paintBuffer(){
console.log("Painting Buffer")
for(var x = 0; x< SCREEN_WIDTH; x++){
for(var y = 0; y< SCREEN_HEIGHT; y++){
ScreenBuffer.stroke(Math.random() * 255)
ScreenBuffer.point(x,y)
}
}
}
Although I am getting a performance improvement, its nowhere near the 30 frames a second I want to be at. Is there a better way to do this?
The only way I can get reasonable performance is by filling up the screen with small squares instead with the following code:
for(var x = 0; x< SCREEN_WIDTH-10; x+=10){
for(var y = 0; y< SCREEN_HEIGHT-10; y+=10){
//ScreenBuffer.stroke(Math.random() * 255)
//ScreenBuffer.point(x,y)
ScreenBuffer.fill(Math.random() * 255);
ScreenBuffer.noStroke()
ScreenBuffer.rect(x,y,10,10)
}
}
But I would really like a pixel effect - ideally to fill the whole screen.
Believe it or not, it's actually the call to stroke() that's slowing down your sketch. You can get around this by setting the value of the pixels directly, using the set() function or accessing the pixels array directly.
More info can be found in the reference, but here's a simple example:
function setup() {
createCanvas(500, 500);
}
function draw() {
for (var i = 0; i < width; i++) {
for (var j = 0; j < height; j++) {
var c = random(255);
set(i, j, c);
}
}
updatePixels();
text(frameRate(), 20, 20);
}
Another approach you might consider is generating a few buffers that contain static images ahead of time, and then using those to draw your static. There's really no need to make the static completely dynamic, so do the work once and then just load from image files or buffers created using the createGraphics() function.
So I'm writing up a processing sketch to test a randomized terrain generator for a scorched earth clone I'm working on. It seems to work as intended but with one minor problem. In the code I generate 800 1 pixel wide rectangles and set the fill to brown beforehand. The combination of the rectangles should be a solid mass with a brown dirt-like color (77,0,0).
However, the combination shows up as black regardless of the rgb fill value set. I think it might have something to do with each rectangle's border being black? Does anyone know what is happening here offhand?
final int w = 800;
final int h = 480;
void setup() {
size(w, h);
fill(0,128,255);
rect(0,0,w,h);
int t[] = terrain(w,h);
fill(77,0,0);
for(int i=0; i < w; i++){
rect(i, h, 1, -1*t[i]);
}
}
void draw() {
}
int[] terrain(int w, int h){
width = w;
height = h;
//min and max bracket the freq's of the sin/cos series
//The higher the max the hillier the environment
int min = 1, max = 6;
//allocating horizon for screen width
int[] horizon = new int[width];
double[] skyline = new double[width];
//ratio of amplitude of screen height to landscape variation
double r = (int) 2.0/5.0;
//number of terms to be used in sine/cosine series
int n = 4;
int[] f = new int[n*2];
//calculating omegas for sine series
for(int i = 0; i < n*2 ; i ++){
f[i] = (int) random(max - min + 1) + min;
}
//amp is the amplitude of the series
int amp = (int) (r*height);
for(int i = 0 ; i < width; i ++){
skyline[i] = 0;
for(int j = 0; j < n; j++){
skyline[i] += ( sin( (f[j]*PI*i/height) ) + cos(f[j+n]*PI*i/height) );
}
skyline[i] *= amp/(n*2);
skyline[i] += (height/2);
skyline[i] = (int)skyline[i];
horizon[i] = (int)skyline[i];
}
return horizon;
}
I think it might have something to do with each rectangle's border being black?
I believe this is the case. In your setup() function, I added the noStroke() function before you draw the rectangles. This removes the black outline to the rectangles. Since each rectangle is only 1 pixel wide, having this black stroke (which is on by default) makes the color of each rectangle black, no matter what color you try to choose before.
Here is an updated setup() function - I now see a reddish brown terrain:
void setup() {
size(w, h);
fill(0, 128, 255);
rect(0, 0, w, h);
int t[] = terrain(w, h);
fill(77, 0, 0);
noStroke(); // here
for (int i=0; i < w; i++) {
rect(i, h, 1, -1*t[i]);
}
}
hello what I'm currently dealing with is the ability to get input from a text file and then convert it into a bitmap and save it to a file.
the input looks like this:
########
# #
########
and I want to draw it using allegro and instead of # there would be pixels of specified size. Each # should represent a tile (10x10 pixel). So the final result would look like this
link to an image
I've actually drawn it using this code:
for (int i = 0; i < 80; i++){
for (int j = 0; j < 10; j++){
al_draw_pixel(i, j, al_map_rgb(0, 0, 0));
}
}
for (int i = 0; i < 10; i++){
for (int j = 10; j < 20; j++){
al_draw_pixel(i, j, al_map_rgb(0, 0, 0));
}
}
for (int i = 70; i < 80; i++){
for (int j = 10; j < 20; j++){
al_draw_pixel(i, j, al_map_rgb(0, 0, 0));
}
}
for (int i = 0; i < 80; i++){
for (int j = 20; j < 30; j++){
al_draw_pixel(i, j, al_map_rgb(0, 0, 0));
}
}
yeah that's pretty bad, so how do I achieve something like that but with a common procedure which would be independent on the text file? thanks for any advice.
note: the only allowed headers are allegro5/allegro.h and allegro5/allegro_image.h
To draw to an image with Allegro 5, you need to do something like:
ALLEGRO_BITMAP *bmp = al_create_bitmap(640, 480);
al_set_target_bitmap(bmp);
Now all of your drawing operations will happen on the image. To later save it:
al_save_bitmap("somefile.bmp", bmp);
You can also use png and jpg as extensions if your image library has support for it enabled.
Use these functions to read the text file:
al_fopen
al_fgetc
al_feof
al_fclose
Set int x and y to zero. You'll be looping over until the end of the file. On every iteration increment x by one. If you reach a new line character (\n) increment y by one and set x to zero. (You should ignore \r characters.)
Now, depending on the character read, draw a tile:
ALLEGRO_BITAMP *tile_to_draw = NULL;
if (c == '#')
tile_to_draw = bmp1;
else if (c == ' ')
tile_to_draw = bmp2;
if (tile_to_draw)
al_draw_bitmap(tile_to_draw, x * 10, y * 10, 0);
Of course there's better ways to map characters to tiles than a series of ifs, but the above works and should be enough to help you finish your homework.
I am trying to build a system that will be able to process a record of someone whistling and output notes.
Can anyone recommend an open-source platform which I can use as the base for the note/pitch recognition and analysis of wave files ?
Thanks in advance
As many others have already said, FFT is the way to go here. I've written a little example in Java using FFT code from http://www.cs.princeton.edu/introcs/97data/. In order to run it, you will need the Complex class from that page also (see the source for the exact URL).
The code reads in a file, goes window-wise over it and does an FFT on each window. For each FFT it looks for the maximum coefficient and outputs the corresponding frequency. This does work very well for clean signals like a sine wave, but for an actual whistle sound you probably have to add more. I've tested with a few files with whistling I created myself (using the integrated mic of my laptop computer), the code does get the idea of what's going on, but in order to get actual notes more needs to be done.
1) You might need some more intelligent window technique. What my code uses now is a simple rectangular window. Since the FFT assumes that the input singal can be periodically continued, additional frequencies are detected when the first and the last sample in the window don't match. This is known as spectral leakage ( http://en.wikipedia.org/wiki/Spectral_leakage ), usually one uses a window that down-weights samples at the beginning and the end of the window ( http://en.wikipedia.org/wiki/Window_function ). Although the leakage shouldn't cause the wrong frequency to be detected as the maximum, using a window will increase the detection quality.
2) To match the frequencies to actual notes, you could use an array containing the frequencies (like 440 Hz for a') and then look for the frequency that's closest to the one that has been identified. However, if the whistling is off standard tuning, this won't work any more. Given that the whistling is still correct but only tuned differently (like a guitar or other musical instrument can be tuned differently and still sound "good", as long as the tuning is done consistently for all strings), you could still find notes by looking at the ratios of the identified frequencies. You can read http://en.wikipedia.org/wiki/Pitch_%28music%29 as a starting point on that. This is also interesting: http://en.wikipedia.org/wiki/Piano_key_frequencies
3) Moreover it might be interesting to detect the points in time when each individual tone starts and stops. This could be added as a pre-processing step. You could do an FFT for each individual note then. However, if the whistler doesn't stop but just bends between notes, this would not be that easy.
Definitely have a look at the libraries the others suggested. I don't know any of them, but maybe they contain already functionality for doing what I've described above.
And now to the code. Please let me know what worked for you, I find this topic pretty interesting.
Edit: I updated the code to include overlapping and a simple mapper from frequencies to notes. It works only for "tuned" whistlers though, as mentioned above.
package de.ahans.playground;
import java.io.File;
import java.io.IOException;
import java.util.Arrays;
import javax.sound.sampled.AudioFormat;
import javax.sound.sampled.AudioInputStream;
import javax.sound.sampled.AudioSystem;
import javax.sound.sampled.UnsupportedAudioFileException;
public class FftMaxFrequency {
// taken from http://www.cs.princeton.edu/introcs/97data/FFT.java.html
// (first hit in Google for "java fft"
// needs Complex class from http://www.cs.princeton.edu/introcs/97data/Complex.java
public static Complex[] fft(Complex[] x) {
int N = x.length;
// base case
if (N == 1) return new Complex[] { x[0] };
// radix 2 Cooley-Tukey FFT
if (N % 2 != 0) { throw new RuntimeException("N is not a power of 2"); }
// fft of even terms
Complex[] even = new Complex[N/2];
for (int k = 0; k < N/2; k++) {
even[k] = x[2*k];
}
Complex[] q = fft(even);
// fft of odd terms
Complex[] odd = even; // reuse the array
for (int k = 0; k < N/2; k++) {
odd[k] = x[2*k + 1];
}
Complex[] r = fft(odd);
// combine
Complex[] y = new Complex[N];
for (int k = 0; k < N/2; k++) {
double kth = -2 * k * Math.PI / N;
Complex wk = new Complex(Math.cos(kth), Math.sin(kth));
y[k] = q[k].plus(wk.times(r[k]));
y[k + N/2] = q[k].minus(wk.times(r[k]));
}
return y;
}
static class AudioReader {
private AudioFormat audioFormat;
public AudioReader() {}
public double[] readAudioData(File file) throws UnsupportedAudioFileException, IOException {
AudioInputStream in = AudioSystem.getAudioInputStream(file);
audioFormat = in.getFormat();
int depth = audioFormat.getSampleSizeInBits();
long length = in.getFrameLength();
if (audioFormat.isBigEndian()) {
throw new UnsupportedAudioFileException("big endian not supported");
}
if (audioFormat.getChannels() != 1) {
throw new UnsupportedAudioFileException("only 1 channel supported");
}
byte[] tmp = new byte[(int) length];
byte[] samples = null;
int bytesPerSample = depth/8;
int bytesRead;
while (-1 != (bytesRead = in.read(tmp))) {
if (samples == null) {
samples = Arrays.copyOf(tmp, bytesRead);
} else {
int oldLen = samples.length;
samples = Arrays.copyOf(samples, oldLen + bytesRead);
for (int i = 0; i < bytesRead; i++) samples[oldLen+i] = tmp[i];
}
}
double[] data = new double[samples.length/bytesPerSample];
for (int i = 0; i < samples.length-bytesPerSample; i += bytesPerSample) {
int sample = 0;
for (int j = 0; j < bytesPerSample; j++) sample += samples[i+j] << j*8;
data[i/bytesPerSample] = (double) sample / Math.pow(2, depth);
}
return data;
}
public AudioFormat getAudioFormat() {
return audioFormat;
}
}
public class FrequencyNoteMapper {
private final String[] NOTE_NAMES = new String[] {
"A", "Bb", "B", "C", "C#", "D", "D#", "E", "F", "F#", "G", "G#"
};
private final double[] FREQUENCIES;
private final double a = 440;
private final int TOTAL_OCTAVES = 6;
private final int START_OCTAVE = -1; // relative to A
public FrequencyNoteMapper() {
FREQUENCIES = new double[TOTAL_OCTAVES*12];
int j = 0;
for (int octave = START_OCTAVE; octave < START_OCTAVE+TOTAL_OCTAVES; octave++) {
for (int note = 0; note < 12; note++) {
int i = octave*12+note;
FREQUENCIES[j++] = a * Math.pow(2, (double)i / 12.0);
}
}
}
public String findMatch(double frequency) {
if (frequency == 0)
return "none";
double minDistance = Double.MAX_VALUE;
int bestIdx = -1;
for (int i = 0; i < FREQUENCIES.length; i++) {
if (Math.abs(FREQUENCIES[i] - frequency) < minDistance) {
minDistance = Math.abs(FREQUENCIES[i] - frequency);
bestIdx = i;
}
}
int octave = bestIdx / 12;
int note = bestIdx % 12;
return NOTE_NAMES[note] + octave;
}
}
public void run (File file) throws UnsupportedAudioFileException, IOException {
FrequencyNoteMapper mapper = new FrequencyNoteMapper();
// size of window for FFT
int N = 4096;
int overlap = 1024;
AudioReader reader = new AudioReader();
double[] data = reader.readAudioData(file);
// sample rate is needed to calculate actual frequencies
float rate = reader.getAudioFormat().getSampleRate();
// go over the samples window-wise
for (int offset = 0; offset < data.length-N; offset += (N-overlap)) {
// for each window calculate the FFT
Complex[] x = new Complex[N];
for (int i = 0; i < N; i++) x[i] = new Complex(data[offset+i], 0);
Complex[] result = fft(x);
// find index of maximum coefficient
double max = -1;
int maxIdx = 0;
for (int i = result.length/2; i >= 0; i--) {
if (result[i].abs() > max) {
max = result[i].abs();
maxIdx = i;
}
}
// calculate the frequency of that coefficient
double peakFrequency = (double)maxIdx*rate/(double)N;
// and get the time of the start and end position of the current window
double windowBegin = offset/rate;
double windowEnd = (offset+(N-overlap))/rate;
System.out.printf("%f s to %f s:\t%f Hz -- %s\n", windowBegin, windowEnd, peakFrequency, mapper.findMatch(peakFrequency));
}
}
public static void main(String[] args) throws UnsupportedAudioFileException, IOException {
new FftMaxFrequency().run(new File("/home/axr/tmp/entchen.wav"));
}
}
i think this open-source platform suits you
http://code.google.com/p/musicg-sound-api/
Well, you could always use fftw to perform the Fast Fourier Transform. It's a very well respected framework. Once you've got an FFT of your signal you can analyze the resultant array for peaks. A simple histogram style analysis should give you the frequencies with the greatest volume. Then you just have to compare those frequencies to the frequencies that correspond with different pitches.
in addition to the other great options:
csound pitch detection: http://www.csounds.com/manual/html/pvspitch.html
fmod: http://www.fmod.org/ (has a free version)
aubio: http://aubio.org/doc/pitchdetection_8h.html
You might want to consider Python(x,y). It's a scientific programming framework for python in the spirit of Matlab, and it has easy functions for working in the FFT domain.
If you use Java, have a look at TarsosDSP library. It has a pretty good ready-to-go pitch detector.
Here is an example for android, but I think it doesn't require too much modifications to use it elsewhere.
I'm a fan of the FFT but for the monophonic and fairly pure sinusoidal tones of whistling, a zero-cross detector would do a far better job at determining the actual frequency at a much lower processing cost. Zero-cross detection is used in electronic frequency counters that measure the clock rate of whatever is being tested.
If you going to analyze anything other than pure sine wave tones, then FFT is definitely the way to go.
A very simple implementation of zero cross detection in Java on GitHub