dpi means nothing for digital images. Digital images are pixels. The dpi setting for a digital image is used when printing to paper. What Tesseract wants is for the text in the image to not be smaller than a certain size. So for a digital image with text, the text within that image needs to be a certain minimal size and not the whole image. The difficulty you are going to have if your use case has variable image sizes (perhaps because taken at different distances or different camera resolutions) is how to normalise these so that the text within them is minimally such that an 'x' character is, say, 100px high. So it's not about changing all your images to 300dpi, that is a red herring - it's about ensuring the text within your images is sufficiently large for Tesseract to work with and that's a problem you'll need to figure out either programmatically or process-driven on capture of the raw image.
On 14 January 2015 at 18:08, newbie <[email protected]> wrote: > The problem is all the images I have seem to be 96dpi, I dont know what > would the height in pts(corresponding to >10pt for 300 dpi) be for the ocr > to accurately detect. Even the upscaled images are in 96 dpi. Any solutions > ? > > On Tuesday, January 13, 2015 at 5:39:02 PM UTC-5, Allistair C wrote: >> >> I wasn't using a formula, just demonstrating that your original text was >> too small. Here is some advice from the FAQ (https://code.google.com/p/ >> tesseract-ocr/wiki/FAQ) >> >> Is there a Minimum Text Size? (It won't read screen text!) >> --- >> There is a minimum text size for reasonable accuracy. You have to >> consider resolution as well as point size. Accuracy drops off below 10pt x >> 300dpi, rapidly below 8pt x 300dpi. A quick check is to count the pixels of >> the x-height of your characters. (X-height is the height of the lower case >> x.) At 10pt x 300dpi x-heights are typically about 20 pixels, although this >> can vary dramatically from font to font. Below an x-height of 10 pixels, >> you have very little chance of accurate results, and below about 8 pixels, >> most of the text will be "noise removed". >> >> On 13 January 2015 at 21:45, newbie <[email protected]> wrote: >> >>> Allistair, >>> Sorry for coming back to you on this again. When I did the >>> upscaling of the original picture to 3000px(like you suggested), ocr could >>> read it. But the resolution on the upscaled picture still seems to be >>> 96.dpi. How did you arrive at the target 3000px ? Did you have a particular >>> formula ? >>> >>> I came up with the exact pixels to be upscaled to, using paint, so that >>> the ocr could read it(trail and error). But I am trying to find the common >>> factor/formula to upscale for any of my images so that the ocr could read >>> it to produce good accuracy. >>> >>> I guess in other words I didnt understand....the below line, in your >>> post below. Any efforts at ellaborating it, is highly appreciated. >>> *it should be a ratio of the original size of the cropped image to make >>> it 300dpi* >>> >>> >>> *Thanks* >>> On Thursday, January 8, 2015 at 5:08:46 PM UTC-5, Allistair C wrote: >>>> >>>> What did the non upscaled version look like - this looks far too >>>> blurred which is why it's struggling. It might be that your upscaling is >>>> too much - it should be a ratio of the original size of the cropped image >>>> to make it 300dpi, rather than always 3000px. >>>> >>>> Cheers >>>> >>>> On 8 January 2015 at 21:34, newbie <[email protected]> wrote: >>>> >>>>> Thanks Allistair. I have it working. The problem is , if I used the >>>>> same "mantra" of resampling for other images its not working. I have this >>>>> cropped image(attached, which is also upscaled to 3000 pixels width vice), >>>>> its coming out VIPZZSO. I need to sharpen this probably. I have to set to >>>>> very sharp in the preprocessing pgm I am using, but in vain. >>>>> >>>>> Any directions. for general preprocessing ? >>>>> >>>>> >>>>> On Thursday, January 8, 2015 at 11:39:55 AM UTC-5, Allistair C wrote: >>>>>> >>>>>> OK good. >>>>>> >>>>>> I got it working by both resampling (upscaling) the cropped version >>>>>> and the full image. >>>>>> >>>>>> If you are using the "white box" approach so that you have a crop >>>>>> area (best method) then you just need to upscale that. >>>>>> >>>>>> There are many ways to resize an image up - you can find that easily >>>>>> with Google. I used Open CV for Android and the cvResize function for >>>>>> example. There are libraries for doing this in Java, .NET, Python etc.. >>>>>> just look around. >>>>>> >>>>>> Cheers >>>>>> >>>>>> On 8 January 2015 at 16:24, newbie <[email protected]> wrote: >>>>>> >>>>>>> It worked YAY!, you have all my gratitude!. ok now I need to know >>>>>>> how you did the resampling. I thought you said you took the cropped >>>>>>> image >>>>>>> and resampled. But this seems like the original png file(Arris2500.png) >>>>>>> resampled. Let me know how you went about resampling and how I can >>>>>>> acheive >>>>>>> it programatically. >>>>>>> >>>>>>> Thanks >>>>>>> >>>>>>> On Thursday, January 8, 2015 11:06:33 AM UTC-5, Allistair C wrote: >>>>>>>> >>>>>>>> Hi, >>>>>>>> >>>>>>>> I've not used tess4j but the JavaDocs show that it should be >>>>>>>> possible to set TessAPI.TessPageSegMode: >>>>>>>> >>>>>>>> http://tess4j.sourceforge.net/docs/docs-1.0/net/sourceforge/ >>>>>>>> tess4j/TessAPI.html >>>>>>>> >>>>>>>> http://tess4j.sourceforge.net/docs/docs-1.2/net/sourceforge/ >>>>>>>> tess4j/TessAPI1.TessPageSegMode.html >>>>>>>> >>>>>>>> The 3000 resampled image was: >>>>>>>> >>>>>>>> https://dl.dropboxusercontent.com/u/523401/ArrisVIP2500_3000.png >>>>>>>> >>>>>>>> Cheers >>>>>>>> >>>>>>>> On 8 January 2015 at 15:35, newbie <[email protected]> wrote: >>>>>>>> >>>>>>>>> Allistair, >>>>>>>>> Thanks for taking the time to respond . Do you know >>>>>>>>> how to use psm 6 in tess4j(its probably an argument to the >>>>>>>>> instantiator, >>>>>>>>> need to look up the src code) ? I have not seen any examples of it >>>>>>>>> being >>>>>>>>> used by googling.. I tried to resample the cropped image to 3000 >>>>>>>>> px(horizontall using paint) like you suggested and ran it thro >>>>>>>>> tess4j and >>>>>>>>> it still did not recognize my model number. Gave me an output of >>>>>>>>> "VIPZSOO". >>>>>>>>> So I guess piping it thro psm 6 is the key. Also can u send me the >>>>>>>>> image >>>>>>>>> that was produced after you resampled it to 3000px, so that I know my >>>>>>>>> resampling is right. >>>>>>>>> >>>>>>>>> I also like your idea of providing the white box in the camera >>>>>>>>> view to use it as my input to cropping . Sure can do that. >>>>>>>>> I think I am glad discussed the feature matching - that seems more >>>>>>>>> like object recognition than text recognition. So probably is far >>>>>>>>> fetched. >>>>>>>>> I had used camFlow(an app) to see if it would recognize my equipment >>>>>>>>> images >>>>>>>>> and it always came back with "Black media player". So they probably >>>>>>>>> are >>>>>>>>> using feature matching of openCV. >>>>>>>>> >>>>>>>>> Thanks again and appreciate your taking time to respond. >>>>>>>>> >>>>>>>>> >>>>>>>>> On Wednesday, January 7, 2015 6:12:05 PM UTC-5, Allistair C wrote: >>>>>>>>>> >>>>>>>>>> It sort of depends on your hardware and how similar or different >>>>>>>>>> they are. Reliable feature matching works on distinct features (so >>>>>>>>>> there >>>>>>>>>> need to be enough points of interest (edges usually) that cover text, >>>>>>>>>> buttons, other bits and pieces). If, for example, all your hardware >>>>>>>>>> was the >>>>>>>>>> same as the example you originally posted and only the model number >>>>>>>>>> was >>>>>>>>>> changing then this would be an issue most likely as the feature >>>>>>>>>> matching >>>>>>>>>> may match several targets. >>>>>>>>>> >>>>>>>>>> Also you mention the tech takes a picture on mobile. Does that >>>>>>>>>> need to be looked up immediately? The issue is that feature matching >>>>>>>>>> is CPU >>>>>>>>>> heavy and can take time on mobile and is a function of the photo >>>>>>>>>> resolution. Luckily, feature matching appears to work better on lower >>>>>>>>>> resolution images and most of the time works in black and white. >>>>>>>>>> Then there >>>>>>>>>> is the potential number of hardware items you are trying to match. >>>>>>>>>> The most >>>>>>>>>> advanced mobile augmented reality products (Metaio, Vuforia) that use >>>>>>>>>> feature matching only allow up to 100 targets to be "tracked" or >>>>>>>>>> "looked >>>>>>>>>> for" at a time - every piece of hardware you are looking for needs >>>>>>>>>> to be >>>>>>>>>> compared to the live input camera view (or photo) and this is the >>>>>>>>>> part that >>>>>>>>>> hits the CPU hard. If however there was an option to offload the >>>>>>>>>> image(s) >>>>>>>>>> to a backend cloud server for feature match or if the tech did not >>>>>>>>>> need an >>>>>>>>>> instant or any kind of result in the field, then you are in a better >>>>>>>>>> situation as you can stand up serious computing power. >>>>>>>>>> >>>>>>>>>> It's not easy to recommend one or the other without all the facts >>>>>>>>>> - as you begin to mention new things like mobile and techs in the >>>>>>>>>> field, >>>>>>>>>> this changes things :) For instance I also used mobile - an Android >>>>>>>>>> tablet, >>>>>>>>>> with Open CV and Tesseract OCR - the combination worked in the field >>>>>>>>>> - the >>>>>>>>>> tech can position the camera face-on to the model number and take a >>>>>>>>>> close >>>>>>>>>> photo. You could even provide a mini App for your techs that has a >>>>>>>>>> basic >>>>>>>>>> cropping tool. The technique I used was to show the camera view in >>>>>>>>>> my app >>>>>>>>>> with a little white transparent box over the camera view that >>>>>>>>>> allowed the >>>>>>>>>> user to position the text to fit that white box. Then, when the >>>>>>>>>> photo was >>>>>>>>>> taken I simply cropped that white box coordinate rectangle and I had >>>>>>>>>> a >>>>>>>>>> perfect match. This was easy vs. feature matching :) >>>>>>>>>> >>>>>>>>>> On Wednesday, 7 January 2015 23:02:09 UTC, newbie wrote: >>>>>>>>>>> >>>>>>>>>>> Sorry for the barrage here. >>>>>>>>>>> The interesting thing is you mentioned feature matching with >>>>>>>>>>> openCV(I dont know anything at all about it). But the one thing is >>>>>>>>>>> I can >>>>>>>>>>> have a repository of these images with me and I need to match it to >>>>>>>>>>> one of >>>>>>>>>>> the user generated image. >>>>>>>>>>> >>>>>>>>>>> A little background might help. I can(or come up with) have a >>>>>>>>>>> repository of all the equipment images with me. A tech might head >>>>>>>>>>> to the >>>>>>>>>>> field, take a picture on his mobile device and I need to match >>>>>>>>>>> it(tech's >>>>>>>>>>> picture) against my repository and come up with the model number. >>>>>>>>>>> >>>>>>>>>>> Is this easier with ocr or feature matching with openCV ? >>>>>>>>>>> >>>>>>>>>>> Thanks >>>>>>>>>>> >>>>>>>>>>> On Wednesday, January 7, 2015 5:35:47 PM UTC-5, newbie wrote: >>>>>>>>>>>> >>>>>>>>>>>> Thanks Allistair , my lucky day as you have responded to both >>>>>>>>>>>> my queries. Let me try to address your questions below and then go >>>>>>>>>>>> ahead >>>>>>>>>>>> with a few of my own :-) >>>>>>>>>>>> >>>>>>>>>>>> *I also meant to ask whether your use case allows for cropping. >>>>>>>>>>>> If you know you will have a certain format of image, cropping an >>>>>>>>>>>> area and >>>>>>>>>>>> resampling should be easy.* >>>>>>>>>>>> Basically the image will be an user generated image, more like >>>>>>>>>>>> the first png file, but we could ask the user to zoom in to the >>>>>>>>>>>> model >>>>>>>>>>>> number, if that would help us indentify the model number.we could >>>>>>>>>>>> do >>>>>>>>>>>> anything with the image(cropping ,resampling etc). But the problem >>>>>>>>>>>> is the >>>>>>>>>>>> model number probably will not be located at the same place for all >>>>>>>>>>>> equipments. >>>>>>>>>>>> >>>>>>>>>>>> 2. Preprocessing - as it should be programatically done would I >>>>>>>>>>>> be using opencv in conjunction with tesseract? I did not see much >>>>>>>>>>>> in >>>>>>>>>>>> tesseract for image processing(I could be totally off). >>>>>>>>>>>> 3.*.I also use psm 6 for these types of image with various >>>>>>>>>>>> text locations.* >>>>>>>>>>>> what is this ? >>>>>>>>>>>> >>>>>>>>>>>> Another thing I probably can come up with is all the model #s >>>>>>>>>>>> or images of all potential equipments, so I have repository to >>>>>>>>>>>> match >>>>>>>>>>>> against. Would that help in any way ? >>>>>>>>>>>> >>>>>>>>>>>> Thanks again for taking the time to respond. Appreciate it. >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> On Wednesday, January 7, 2015 4:44:47 PM UTC-5, Allistair C >>>>>>>>>>>> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>> I also meant to ask whether your use case allows for cropping. >>>>>>>>>>>>> If you know you will have a certain format of image, cropping an >>>>>>>>>>>>> area and >>>>>>>>>>>>> resampling should be easy. You could also do some preprocessing >>>>>>>>>>>>> that looks >>>>>>>>>>>>> for certain icons in your image to get some context as to where >>>>>>>>>>>>> the model >>>>>>>>>>>>> number is likely to be (see feature matching on Open CV). >>>>>>>>>>>>> However, I would >>>>>>>>>>>>> need to know more about your use case. >>>>>>>>>>>>> >>>>>>>>>>>>> That said, resampling your full image to 3000px wide yielded a >>>>>>>>>>>>> result with a full model number but the more you can crop the >>>>>>>>>>>>> area the >>>>>>>>>>>>> better the result: >>>>>>>>>>>>> >>>>>>>>>>>>> AT&T U verse ‘ § >>>>>>>>>>>>> LINK HD nzc , >>>>>>>>>>>>> rowzn Q I ‘ .» . ‘ nsuu 4 0|: > I >>>>>>>>>>>>> / sj J \ >>>>>>>>>>>>> VIP2500 °%' 7 A R R I s >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> On 7 January 2015 at 21:39, Allistair <[email protected]> >>>>>>>>>>>>> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>>> A common technique is to pre-process your input image. >>>>>>>>>>>>>> >>>>>>>>>>>>>> Resizing produced good results.I also use psm 6 for these >>>>>>>>>>>>>> types of image with various text locations. >>>>>>>>>>>>>> >>>>>>>>>>>>>> In this case I first used your cropped image: >>>>>>>>>>>>>> >>>>>>>>>>>>>> tesseract ArrisVIP2500_cropped.png out -l eng -psm 6 config >>>>>>>>>>>>>> >>>>>>>>>>>>>> and got: >>>>>>>>>>>>>> >>>>>>>>>>>>>> AT&T U verse >>>>>>>>>>>>>> rowsn >>>>>>>>>>>>>> O F3. >>>>>>>>>>>>>> vrrzsoo ’e' >>>>>>>>>>>>>> >>>>>>>>>>>>>> Then I resampled your image to 2000px wide: >>>>>>>>>>>>>> >>>>>>>>>>>>>> tesseract ArrisVIP2500_cropped_2000.png out2000 -l eng -psm 6 >>>>>>>>>>>>>> config >>>>>>>>>>>>>> >>>>>>>>>>>>>> and got: >>>>>>>>>>>>>> >>>>>>>>>>>>>> AT&T U verse >>>>>>>>>>>>>> POWER © " ‘| >>>>>>>>>>>>>> / ‘j""'j"’.. >>>>>>>>>>>>>> VIP2500 '%’ >>>>>>>>>>>>>> >>>>>>>>>>>>>> Cheers >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> On 7 January 2015 at 19:26, newbie <[email protected]> >>>>>>>>>>>>>> wrote: >>>>>>>>>>>>>> >>>>>>>>>>>>>>> I am using tess4j, a java wrapper around tesseract and Here >>>>>>>>>>>>>>> are the images and results. The intent is to extract >>>>>>>>>>>>>>> VIP2500(model number) >>>>>>>>>>>>>>> from the image. An help is appreciated. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Attached are the original png file ( >>>>>>>>>>>>>>> ArrisVIP2500.png),binarized file(ArrisVIP2500_bin.TIF) and then >>>>>>>>>>>>>>> a zoomed >>>>>>>>>>>>>>> and cropped file(ArrisVIP2500_cropped.png). >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> *ArrisVIP2500.png* >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> é ATE-T U-verse >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> rowan 0 >>>>>>>>>>>>>>> / >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> *ArrisVIP2500_bin.TIF* >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> AT&T U-verse >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> rowan <3 3 >>>>>>>>>>>>>>> / -- >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> vxvzsoo ‘Q’ >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> *ArrisVIP2500_cropped.png* >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> ATE-T U-verse >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> rowsn Q >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> VIPZSOO ‘e’ This looks the closest to >>>>>>>>>>>>>>> VIP2500 , I need to get tess4j to reconginze digits, that said, >>>>>>>>>>>>>>> this might >>>>>>>>>>>>>>> not be a realistic scenario, as someone/something >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Needs to zoom and >>>>>>>>>>>>>>> crop the image before hand(preprocessing). >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> -- >>>>>>>>>>>>>>> You received this message because you are subscribed to the >>>>>>>>>>>>>>> Google Groups "tesseract-ocr" group. >>>>>>>>>>>>>>> To unsubscribe from this group and stop receiving emails >>>>>>>>>>>>>>> from it, send an email to [email protected]. >>>>>>>>>>>>>>> To post to this group, send email to >>>>>>>>>>>>>>> [email protected]. >>>>>>>>>>>>>>> Visit this group at http://groups.google.com/group >>>>>>>>>>>>>>> /tesseract-ocr. >>>>>>>>>>>>>>> To view this discussion on the web visit >>>>>>>>>>>>>>> https://groups.google.com/d/msgid/tesseract-ocr/009ffbc7-90c >>>>>>>>>>>>>>> c-417a-90c8-b4ac9b5bb203%40googlegroups.com >>>>>>>>>>>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/009ffbc7-90cc-417a-90c8-b4ac9b5bb203%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>>>>>>>>>>> . >>>>>>>>>>>>>>> For 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