Thanks Elmer for your answer. I have your same problem, i have read in
real time a sequence of number. I tried to binarize an image of plate
in black and white using gimp with a statical threshold but with bad
results. What filters you have used to clear the image? and the
quality of your image is poor as mine?

On 10 Mag, 22:32, Elmer Fittery <[email protected]> wrote:
> This is what I am doing now!
>
> I take a 72x72 resolution screen shot of a section of my screen.
>
> In one case the picture is black background and white foreground.
> In the other case the screen shot is a white background with a black
> foreground.
>
> The only thing I am trying to process is $.,0123456789
>
> In general, with preprocessing of the .tif file with Imagick's convert
> program, I have no problems with using tesseract to convert the image to
> text.
>
> So, my observation about the 72x72 pixels/inch being too poor for
> tessseract to process is:
>
> It is not true.
>
> Also you can use the Imagick command:
>
> convert <input-file-name> -resample 300x300 <output-file-name>
>
> and your output file will have a 300x300 resolution.
>
> If you don't believe it, use the command:
>
> tiffinfo <file-basename>.tif
>
> NOTE:  you really need to preprocess the .tif file to make it a
> black/white .tif file - i.e. get rid of any RGB colors.
>
> The real key to getting good results with tesseract is to clean the file
> up with a graphic program prior to trying to convert it to text.
>
> I spent the last 2 weeks developing code to in real time take screen
> shots of numbers; cleaning up screen shot; converting to numbers;
> passing the numbers to a math routine to do statistical calculations.
>
> It can be done, but it is a pain.  If I didn't have tesseract and
> Imagick, it would be impossible.
>
> good luck
>
>
>
> On Mon, 2010-05-10 at 23:11 +0530, Sriranga(77yrsold) wrote:
> > Tif file if very poor resolution and background is not deep black and
> > white Tesseract will not support such type of tif. sorry.
>
> > On Mon, May 10, 2010 at 5:55 PM, faster589 <[email protected]>
> > wrote:
> >         Thanks for your answer. I using ubuntu 9.10 for run tesseract.
> >         I have upload the two file t0.tif e t0.box in the section file
> >         that i
> >         use for training tesseract.
> >         the two link are:
>
> >        
> > http://tesseract-ocr.googlegroups.com/web/t1.box?gda=OJOMSDgAAADSWFpg...
>
> >        
> > http://tesseract-ocr.googlegroups.com/web/t1.tif?gda=WGUDjzgAAADSWFpg...
>
> >         image resolution is too low to using with tesseract?
> >         I have create manually the file .box because tesseract with
> >         the
> >         command "tesseract fontfile.tif fontfile batch.nochop makebox"
> >         return
> >         an empty file.
>
> >         On 10 Mag, 04:01, "Sriranga(77yrsold)"
> >         <[email protected]>
> >         wrote:
>
> >         > Which OS is using? It appears that resolution=72 is poor -
> >         it should be more
> >         > than 300 dpi - try again.
> >         > One more thing the commandline should be like this
> >         > "tesseract fontfile.tif fontfile nobatch box.train.stderr",
> >         if you are using
> >         > tesseract svn-319 otherwise is OK.
> >         >  please upload sample tif file with its box.
> >         > Cheers.
>
> >         > On Mon, May 10, 2010 at 12:44 AM, faster589
> >         <[email protected]> wrote:
> >         > > Hi ! I'm training tesseract for character plate
> >         recognition. I have
> >         > > create the two file image.tif and image.box for training
> >         tesseract but
> >         > > when i lunch the command tesseract fontfile.tif junk
> >         nobatch
> >         > > box.train.stderr tesseract return this error:
>
> >         > > Tesseract Open Source OCR Engine
> >         > > Image has 8 * 3 bits per pixel, and size (640,480)
> >         > > Resolution=72
> >         > > APPLY_BOXES: boxfile 1/1/C ((188,216),(218,272)): FAILURE!
> >         box
> >         > > overlaps no blobs or blobs in multiple rows
> >         > > APPLY_BOXES: boxfile 1/2/C ((220,216),(253,272)): FAILURE!
> >         box
> >         > > overlaps no blobs or blobs in multiple rows
> >         > > APPLY_BOXES: boxfile 1/3/1 ((274,215),(299,273)): FAILURE!
> >         box
> >         > > overlaps no blobs or blobs in multiple rows
> >         > > APPLY_BOXES: boxfile 1/4/5 ((304,217),(337,274)): FAILURE!
> >         box
> >         > > overlaps no blobs or blobs in multiple rows
> >         > > APPLY_BOXES: boxfile 1/5/4 ((337,217),(367,273)): FAILURE!
> >         box
> >         > > overlaps no blobs or blobs in multiple rows
> >         > > APPLY_BOXES: boxfile 1/6/B ((369,215),(401,273)): FAILURE!
> >         box
> >         > > overlaps no blobs or blobs in multiple rows
> >         > > APPLY_BOXES: boxfile 2/1/E ((399,216),(434,274)): FAILURE!
> >         box
> >         > > overlaps no blobs or blobs in multiple rows
> >         > > APPLY_BOXES: More than one block??
> >         > > APPLY_BOXES: FATALITY - 0 labelled samples of "C" - target
> >         is 2:
> >         > > C:[43]
> >         > > APPLY_BOXES: FATALITY - 0 labelled samples of "1" - target
> >         is 1:
> >         > > 1:[31]
> >         > > APPLY_BOXES: FATALITY - 0 labelled samples of "5" - target
> >         is 1:
> >         > > 5:[35]
> >         > > APPLY_BOXES: FATALITY - 0 labelled samples of "4" - target
> >         is 1:
> >         > > 4:[34]
> >         > > APPLY_BOXES: FATALITY - 0 labelled samples of "B" - target
> >         is 1:
> >         > > B:[42]
> >         > > APPLY_BOXES: FATALITY - 0 labelled samples of "E" - target
> >         is 1:
> >         > > E:[45]
> >         > > APPLY_BOXES:
> >         > >   Boxes read from boxfile:       7
> >         > >   Initially labelled blobs:      0 in 0 rows
> >         > >   Box failures detected:                    7
> >         > >   Duped blobs for rebalance:     0
> >         > >   "C" has fewest samples:     0
> >         > >                                Total unlabelled words:
> >              0
> >         > >                                Final labelled words:
> >              0
> >         > > Generating training data
> >         > > Generated training data for 0 blobs
>
> >         > > How can i solve?
>
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