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For the purposes of this tutorial, you can use this sample black-and-white excerpt: require 'rubygems' require 'rmagick' img = Magick:: Image::read('1.tif').first # Your mileage will vary with this following method; we ended up just using a Photoshop batch job to correctly produce a # black-and-white version img = img.sigmoidal_contrast_channel(5,40,true).quantize(16, Magick:: GRAYColorspace).posterize(5) # write out the result just to see what it looks like img.write('bw-1.tif') # the block sets the saved image to a depth of 8-bits Detecting the lines in the file simply involves finding the lines in which all the pixels are non-white (some may be gray, which you'll see if you zoom in at the pixel level).
This can be done with using RMagick's get_pixels method on every horizontal and vertical line; get_pixels returns an array of pixels within the boundaries we specify.
In the previous code, we're essentially stepping through the image column by column, line by line.
If you subscribe to any of our print newsletters and have never activated your online account, please activate your account below for online access.So, in the above code, we simply run Tesseract on each TIFF as it is created.Add this to the above code, after the constitute call: Now you should have nearly 500 text files in cell-files.RMagick's Pixel class has red, blue, and green attributes.Examining the red, blue, and green values of white pixel should give you 65535 for each; a black pixel will return the value 0. So first we crop the image to remove the white space surrounding the table (using bounding_box).
Then we examine each pixel of a line and record the positions where every pixel in that line had color values less than a dark gray (63000 seems to be enough tolerance): box = img.bounding_box img.crop!