问题
I've never used OpenCV before, but I'm trying to write my neural network system to recognize text and I need some tool for text extraction/ segmentation.
How can I use java OpenCV to preprocess and segmentate an image containing text.
I don't need to recognize the text, I just need to get each letter in a separate image.
Something like this :
回答1:
Try this code .No need of OpenCV
import java.awt.image.BufferedImage;
import java.util.ArrayList;
import java.util.List;
import org.neuroph.imgrec.ImageUtilities;
public class CharExtractor {
private int cropTopY = 0;//up locked coordinate
private int cropBottomY = 0;//down locked coordinate
private int cropLeftX = 0;//left locked coordinate
private int cropRightX = 0;//right locked coordinate
private BufferedImage imageWithChars = null;
private boolean endOfImage;//end of picture
private boolean endOfRow;//end of current reading row
/**
* Creates new char extractor with soecified text image
* @param imageWithChars - image with text
*/
public CharExtractor(BufferedImage imageWithChars) {
this.imageWithChars = imageWithChars;
}
public void setImageWithChars(BufferedImage imageWithChars) {
this.imageWithChars = imageWithChars;
}
/**
* This method scans image pixels until it finds the first black pixel (TODO: use foreground color which is black by default).
* When it finds black pixel, it sets cropTopY and returns true. if it reaches end of image and does not find black pixels,
* it sets endOfImage flag and returns false.
* @return - returns true when black pixel is found and cropTopY value is changed, and false if cropTopY value is not changed
*/
private boolean findCropTopY() {
for (int y = cropBottomY; y < imageWithChars.getHeight(); y++) { // why cropYDown? - for multiple lines of text using cropBottomY from previous line above; for first line its zero
for (int x = cropLeftX; x < imageWithChars.getWidth(); x++) { // scan starting from the previous left crop position - or it shoud be right???
if (imageWithChars.getRGB(x, y) == -16777216) { // if its black rixel (also consider condition close to black or not white or different from background)
this.cropTopY = y; // save the current y coordiante
return true; // and return true
}
}
}
endOfImage = true; //sets this flag if no black pixels are found
return false; // and return false
}
/**
* This method scans image pixels until it finds first row with white pixels. (TODO: background color which is white by default).
* When it finds line whith all white pixels, it sets cropBottomY and returns true
* @return - returns true when cropBottomY value is set, false otherwise
*/
private boolean findCropBottomY() {
for (int y = cropTopY + 1; y < imageWithChars.getHeight(); y++) { // scan image from top to bottom
int whitePixCounter = 0; //counter of white pixels in a row
for (int x = cropLeftX; x < imageWithChars.getWidth(); x++) { // scan all pixels to right starting from left crop position
if (imageWithChars.getRGB(x, y) == -1) { // if its white pixel
whitePixCounter++; // increase counter
}
}
if (whitePixCounter == imageWithChars.getWidth()-1) { // if we have reached end of line counting white pixels (x pos)
cropBottomY = y;// that means that we've found white line, so set current y coordinate minus 1
return true; // as cropBottomY and finnish with true
}
if (y == imageWithChars.getHeight() - 1) { // if we have reached end of image
cropBottomY = y; // set crop bottom
endOfImage = true; // set corresponding endOfImage flag
return true; // and return true
}
}
return false; // this should never happen, however its possible if image has non white bg
}
private boolean findCropLeftX() {
int whitePixCounter = 0; // white pixel counter between the letters
for (int x = cropRightX; x < imageWithChars.getWidth(); x++) { // start from previous righ crop position (previous letter), and scan following pixels to the right
for (int y = cropTopY; y <= cropBottomY; y++) { // vertical pixel scan at current x coordinate
if (imageWithChars.getRGB(x, y) == -16777216) { // when we find black pixel
cropLeftX = x; // set cropLeftX
return true; // and return true
}
}
// BUG?: this condition looks strange.... we might not need whitePixCounter at all, it might be used for 'I' letter
whitePixCounter++; // if its not black pixel assume that its white pixel
if (whitePixCounter == 3) { // why 3 pixels? its hard coded for some case and does not work in general...!!!
whitePixCounter = 0; // why does it sets to zero, this has no purporse at all...
}
}
endOfRow = true; // if we have reached end of row and we have not found black pixels, set the endOfRow flag
return false; // and return false
}
/**
* This method scans image pixels to the right until it finds next row where all pixel are white, y1 and y2.
* @return - return true when x2 value is changed and false when x2 value is not changed
*/
private boolean findCropRightX() {
for (int x = cropLeftX + 1; x < imageWithChars.getWidth(); x++) { // start from current cropLeftX position and scan pixels to the right
int whitePixCounter = 0;
for (int y = cropTopY; y <= cropBottomY; y++) { // vertical pixel scan at current x coordinate
if (imageWithChars.getRGB(x, y) == -1) { // if we have white pixel at current (x, y)
whitePixCounter++; // increase whitePixCounter
}
}
// this is for space!
int heightPixels = cropBottomY - cropTopY; // calculate crop height
if (whitePixCounter == heightPixels+1) { // if white pixel count is equal to crop height+1 then this is white vertical line, means end of current char/ (+1 is for case when there is only 1 pixel; a 'W' bug fix)
cropRightX = x; // so set cropRightX
return true; // and return true
}
// why we need this when we allready have condiiton in the for loop? - for the last letter in the row.
if (x == imageWithChars.getWidth() - 1) { // if we have reached end of row with x position
cropRightX = x; // set cropRightX
endOfRow = true; // set endOfRow flag
return true; // and return true
}
}
}
public List<BufferedImage> extractCharImagesToRecognize() {
List<BufferedImage> trimedImages = new ArrayList<BufferedImage>();
int i = 0;
while (endOfImage == false) {
endOfRow = false;
boolean foundTop = findCropTopY();
boolean foundBottom = false;
if (foundTop == true) {
foundBottom = findCropBottomY();
if (foundBottom == true) {
while (endOfRow == false) {
boolean foundLeft = false;
boolean foundRight = false;
foundLeft = findCropLeftX();
if (foundLeft == true) {
foundRight = findCropRightX();
if (foundRight == true) {
BufferedImage image = ImageUtilities.trimImage(ImageUtilities.cropImage(imageWithChars, cropLeftX, cropTopY, cropRightX, cropBottomY));
trimedImages.add(image);
i++;
}
}
}
cropLeftX = 0;
cropRightX = 0;
}
}
}
cropTopY = 0;
cropBottomY = 0;
endOfImage = false;
return trimedImages;
}
public static void main(String[] args) throws Exception {
File f=new File("./written.png");
BufferedImage img=ImageIO.read(f);
CharExtractor ch=new CharExtractor(img);
List<BufferedImage> list=ch.extractCharImagesToRecognize();
for(int i=0;i<list.size();i++)
{
File outputfile = new File("./char_" +i+ ".png");
ImageIO.write(list.get(i),"png", outputfile);
}
}
}
回答2:
What you are trying to do is a general scene text localization problem, and it's pretty difficult. Check out this article for inspiration - http://www.maseltov.eu/wp-content/uploads/2014/02/CTU-03_Real-Time-Scene-Text-Localization-and-Recognition.pdf
What you could do is:
- write a program which extracts MSER objects from an image
- extract features from every patch determined by each individual MSER (which features is outlined in the article)
- train your classifier (in your case a neural network I guess?) so that it is able to distinguish between character and non-character regions
- write a program which uses your classifier to extract MSERs and classify them using the trained NN.
The MSER algorithm is implemented in OpenCV, so that is a plus. There are also neural network classifiers there, but since I only used SVM, I can not comment on that too much. I should say that we had to solve this problem as well and it is perfectly possible to do so using OpenCV. Just don't expect to get everything on a silver platter - there is a lot of work involved; especially when choosing and extracting the blob features.
回答3:
I am not familiar with neural networks, but if you just want to find letters in an image with respecting scale and rotation, I can recommend this Project http://www.codeproject.com/Articles/196168/Contour-Analysis-for-Image-Recognition-in-C It is written in C#, but you could port it to java or at least get a good amount of insights on this topic.
来源：https://stackoverflow.com/questions/22879005/text-extraction-and-segmentation-open-cv