converting cv::Mat for tesseract

Question

I'm using OpenCV to extract a subimage of a scanned document and would like to use tesseract to perform OCR over this subimage.

I found out that I can use two methods for text recognition in tesseract, but so far I wasn't able to find a working solution.

A.) How can I convert a cv::Mat into a PIX*? (PIX* is a datatype of leptonica)

Based on vasiles code below, this is essentially my current code:

 cv::Mat image = cv::imread("c:/image.png"); 
 cv::Mat subImage = image(cv::Rect(50, 200, 300, 100)); 

 int depth;
 if(subImage.depth() == CV_8U)
    depth = 8;
 //other cases not considered yet

 PIX* pix = pixCreateHeader(subImage.size().width, subImage.size().height, depth);
 pix->data = (l_uint32*) subImage.data; 

 tesseract::TessBaseAPI tess;
 STRING text; 
 if(tess.ProcessPage(pix, 0, 0, &text))
 {
    std::cout << text.string(); 
 }   

While it doesn't crash or anything, the OCR result still is wrong. It should recognize one word of my sample image, but instead it returns some non-readable characters.

The method PIX_HEADER doesn't exist, so I used pixCreateHeader, but it doesn't take the number of channels as an argument. So how can I set the number of channels?

B.) How can I use cv::Mat for TesseractRect() ?

Tesseract offers another method for text recognition with this signature:

char * TessBaseAPI::TesseractRect   (   
    const UINT8 *   imagedata,
    int     bytes_per_pixel,
    int     bytes_per_line,
    int     left,
    int     top,
    int     width,
    int     height   
)   

Currently I am using the following code, but it also returns non-readable characters (although different ones than from the code above.

char* cr = tess.TesseractRect(
           subImage.data, 
           subImage.channels(), 
           subImage.channels() * subImage.size().width, 
           0, 
           0, 
           subImage.size().width, 
           subImage.size().height);   

Answer 1

tesseract::TessBaseAPI tess; 
cv::Mat sub = image(cv::Rect(50, 200, 300, 100));
tess.SetImage((uchar*)sub.data, sub.size().width, sub.size().height, sub.channels(), sub.step1());
tess.Recognize(0);
const char* out = tess.GetUTF8Text();