opencv--recognition of handwritten numerals

This is a Raspberry Pi run, opencv3.

OPENCV provides a handwritten digital picture to us, as shown, as a sample library for identifying handwritten numbers.

0 to 9 A total of 10 numbers, each number has five lines, a row of 100 digits. First of all, we need to intercept these 5,000 numbers.

The picture size is 1000*2000, and each number block size is 20*20.

1. Intercept samples and store

The following code is the process of intercepting the above numbers and storing them in a matrix

The training data, generally will be two matrices, one matrix holds the data image, the other matrix holds the data image corresponding number

Mat src = imread ("Sample.png");    Mat Grayimage;    Cvtcolor (SRC, grayimage, cv_bgr2gray); Threshold (Grayimage, Grayimage, -,255, cv_thresh_binary); intp = -;//a number size of 20*20    intm = grayimage.rows/p;//number of numbers in a rampage m    intn = grayimage.cols/p;//Number of columns in the column nMat data, labels;//Data is stored in the sample, and the label is the number corresponding to a data sample.     for(inti =0; I < n; i++){        inty = i * p;//position of the beginning of the first digit of the vertical column         for(intj =0; J < M; J + +){            intx = J * p;//the position of the first number of rowsMat DST; Grayimage (Range (x,x+ P), Range (y, y +p)).                        CopyTo (DST); Data.push_back (Dst.reshape (0,1));//change 20*20 size matrix to 1*400 vectorLabels.push_back (J/5);//numbers that correspond to the data vectors stored}} data.convertto (data, cv_32f); //changing the data type of a pixel to a floating-point typeMat Traindata, trainlabels; Traindata= Data (Range (0, the), Range::all ()); Trainlabels= Labels (Range (0, the), Range::all ());

2. Processing images of numbers to be identified

//processing generation detection ImagesMat Image, DST; Image= Imread ("6.png");    Cvtcolor (image, image, Color_bgr2gray); Threshold (image, image, -,255, CV_THRESH_BINARY_INV); Imshow ("Image", Image);    Image.copyto (DST); Vector< vector<point> >contours; Vector<Vec4i>hierarchy;    Findcontours (image,contours, Hierarchy, cv_retr_external, cv_chain_approx_none); Vector<Point> point = contours[0]; Rect rect=Boundingrect (point); intx = rect.x, y =Rect.y; intH=rect.height, W =Rect.width; Mat Now= DST (Range (x, x+h-1), Range (Y, y+w-1)); //DST (rect). CopyTo (now);Resize (Now,now,size ( -, -));

3. Use the KNN algorithm to identify the image to be recognized as a training sample of the same processing

I am running the program, has been the following error, changed several ways to deal with the picture, still no use

mat_<float>  nums;    Nums  = Now.reshape (0,1);    Nums.convertto (Nums, cv_32f);    Imshow (" image to be measured ", now)   ; /* Mat mm;     Mm.push_back (Now.reshape (0,1));     Mm.convertto (mm,cv_32f);     Mat nums = mm (Range (0,1), Range::all ());     /*float imagedata[20*20];     for (int i =0; i <, i++) {for       (int j=0;j<20;j++) {                      imagedata[i *20 +j] = now.data[i *20+j];         }   }     Mat Nums (1,20*20, cv_32f, imagedata); */

The last view of the source code finds no other parameters:

  Error Knn->findnearest (nums, 1, Mat ());  1, temp); // to pass in a specific mat type    

The final identification code is

// Create a KNN classifier    ptr<ml::knearest>  KNN = (Ml::knearest::create ());     KNN->setisclassifier (true);    Ptr<ml::TrainData> tdata = ml::traindata::create (traindata,ml::row_sample, trainlabels);    KNN---Train (tdata);    Mat temp;     float 1 , temp);         << result<<endl;

Check it out many times and just can't identify all

Program defect: Image processing problem to be detected. Cannot intercept a suitable ROI region

Let's improve.

opencv--recognition of handwritten numerals