Digitize books: Searchable OCR PDF with text overlay from scanned or photographed books on Linux

Here is my method to digitize books. It is a tutorial about how to produce searchable, OCR (Optical Character Recognition) PDFs from a hardcopy book using free software tools on Linux distributions. You probably can find more convenient proprietary software, but that’s not the objective of this post.

Important: I should not need to mention that depending on the copyright attached to a particular work, you may not be allowed to digitize it. Please inform yourself before, so that you don’t break copyright laws!!!

Digitize books

To scan a book, you basically have 2 choices:

  1. Scan each double page with a flatbed scanner
  2. Take a good photo camera, mount it on a tripod, have it point vertically down on the book, and then take photos of each double page. Professional digitizers use this method due to less strain on the originals.

No matter which method, the accuracy of OCR increases with the resolution and contrast of the images. The resolution should be high enough so that each letter is at least 25 pixels tall.

Since taking a photo is almost instant, you can be much faster with the photographing method than using a flatbed scanner. This is especially true for voluminous books which are hard to repeatedly take on and off a scanner. However, getting sharp high-resolution images with a camera is more difficult than using a flatbed scanner. So it’s a tradeoff that depends on your situation, equitpment and your skills.

Using a flatbed scanner doesn’t need explanation, so I’ll only explain the photographic method next.

Photographing each page

Digitizing books (International Dunhuang Project, CC BY-SA 3.0)
Digitizing books
(International Dunhuang Project, CC BY-SA 3.0)

If you use a camera, and you don’t have some kind of remote trigger or interval-trigger at hand, you would need 2 people: someone who operates the camera, and another one who flips the pages. You can easily scan 1 double page every 2 seconds once you get more skilled in the process.

Here are the steps:

  • Set the camera on a tripod and have it point vertically down. The distance between camera and book should be at least 1 meter to approximate orthagonal projection (imitates a flatbed scanner). Too much perspective projection would skew the text lines.
  • Place the book directly under the camera – avoid pointing the camera at any non-90-degree angles that would cause perspective skewing of the contents. Later we will unskew the images, but the less skewing you get at this point, the better.
  • Set up uniform lighting, as bright as you are able. Optimize lighting directions to minimize possible shadows (especially in the book fold). Don’t place the lights near the camera or it will cause reflections on paper or ink.
  • Set the camera to manual mode. Use JPG format. Turn the camera flash off. All pictures need to have uniform exposure characteristics to make later digital processing easier.
  • Maximize zoom so that a margin of about 1 cm around the book is still visible. This way, aligning of the book will take less time. The margin will be cropped later.
  • Once zoom and camera position is finalized, mark the position of the book on the table with tape. After moving the book, place it back onto the original position with help of these marks.
  • Take test pictures. Inspect and optimize the results by finding a balance between the following camera parameters:
    • Minimize aperture size (high f/value) to get sharper images.
    • Maximize ISO value to minimize exposure time so that wiggling of the camera has less of an effect. Bright lighting helps lowering ISO which helps reducing noise.
    • Maximize resolution so that the letter size in the photos is at least 25 pixels tall. This will be important to increase the quality of the OCR step below, and you’ll need a good camera for this.
  • Take one picture of each double page.
One double page of a book that will be digitized. This is actually a scan, but you also can use a good photo camera. Note that the right page is slighty rotated.
One double page of a book that will be digitized. This is actually a scan, but you also can use a good photo camera. Make sure that letters are at least 25 pixels tall. Note that the right page is slighty rotated.

Image Preprocessing

Let’s remember our goal: We want a PDF …

  • which is searchable (the text should be selectable)
  • whose file size is minimized
  • has the same paper size as the original
  • is clearly legible

The following steps are the preprocessing steps to accomplish this. We will use ImageMagick command line tools (available for all platforms) and a couple of other software, all available for Linux distributions.

A note on image formats

Your input files can be JPG or TIFF, or whatever format your scanner or camera support. However, this format must also be supported by ImageMagick. We’ll convert these images to black-and-white PBM images to save space and speed up further processing. PBM is a very simple, uncompressed image format that only stores 1 bit per pixel (2 colors). This image format can be embedded into the PDF directly, and it will be losslessly compressed extremely well, resulting in the smallest possible PDF size.

Find processing parameters by using just a single image

Before we will process all the images as a batch, we’ll just pick one image and find the right processing parameters. Copy one photograph into a new empty folder and do the following steps.

Converting to black and white

Suppose we have chosen one image in.JPG. Run:

Inspect the generated 1blackwhite.pbm file. Optimize the parameters threshold (50% in above example), brightness (0 in above example), and contrast (10 in above example) for best legibiligy of the text.

Black-white conversion of the original image. Contrast and resolution is important.
Black-white conversion of the original image. Contrast and resolution is important.

Cropping away the margins

Next we will crop away the black borders so that the image will correspond to the paper size.

In this example, the cropped image will be a rectangle of 2400×2000 pixels, taken from the offset 760,250 of the input image. Inspect 2cropped.pbm until you get the parameters right, it will be some trial-and-error. The vertical book fold should be very close to the horizontal middle of the cropped image (important for next step).

The cropped image
The cropped image

Split double pages into single pages

This will generate 2 images. Inspect  split0001.pbm and split0002.pbm. You only can use 50% of horizontal cut, otherwise you’ll get more than 2 images.

Left split page
Left split page
Right split page
Right split page

Deskewing the image

Your text lines are probably not exactly horizontal (page angles, camera angles, perspective distortion, etc.). However, having exactly horizontal text lines is very important for accuracy of OCR software. We can deskew an image with the following command:

Inspect the output file 3deskewed.pbm for best results.

The deskewed left page
The deskewed left page
The deskewed right page. Notice that the text lines are now perfectly horizontal. However, deskewing can have its limits, so the original image should already be good!
The deskewed right page. Notice that the text lines are now perfectly horizontal. However, deskewing can have its limits, so the original image should already be good!

Process all the images

Now that you’ve found the paramters that work for you, it’s simple to convert all of your images as a batch, by passing all the paramters at the same time to convert. Run the following in the folder where you stored all the JPG images (not in the folder where you did the previous single-image tests):

Now, for each .JPG input file, we’ll have two  .pbm output files. Inspect all .pbm files and make manual corrections if needed.

Note: If you have black borders on the pages, consider using unpaper to remove them. I’ll save writing about using unpaper for a later time.


Producing OCR PDFs with text overlay

The tesseract OCR engine can generate PDFs with a selectable text layer directly from our PBM images. Since OCR is CPU intensive, we’ll make use of parallel processing on all of our CPU cores with the parallel tool. You can install both by running


For each PBM file, create one PDF file:

To merge all the PDF files into one, run pdfunite from the poppler-utils package:

Success! And this is our result:

The PDF has been OCR'd and a selectable text layer has been generated
The PDF has been OCR’d and a selectable text layer has been generated