Alyn

Skew detection and correction in images containing text

Image with skew

Image after deskew

Install and use via pip!

Recommended way(using virtualenv):

mkdir alyn-test
cd alyn test
mkvirtualenv .
pip install alyn
source bin/activate

To detect skew angle in image:

from alyn import SkewDetect
sd = SkewDetect(
	input_file='path_to_file',
	batch_path='optional_batch_processing_path',
	output_file='optional_text_file_output_path',
	display_output='Yes/No')
sd.run()

Extra options:

sigma:canny edge detection blurring
plot_hough: display hough lines detected
num_peaks: control the number of hough line peaks

To deskew image:

from alyn import Deskew
d = Deskew(
	input_file='path_to_file',
	display_image='preview the image on screen',
	output_file='path_for_deskewed image',
	r_angle='offest_angle_in_degrees_to_control_orientation')`
d.run()

Requires

numpy
matplotlib
scipy
scikit-image

Techniques used

Canny Edge Detection
Hough Transform

Features

Detect the skew in given images
Display the output
Save the output to txt file
Batch process files in a directory
View Hough Transform of a given image
Set the number of peaks for Hough Transform and Sigma for Canny Edge detection
Rotate the image to remove the skew

How the skew detection works

The skew detection script takes image file as input, then performs the following steps:

Converts the image to greyscale
Performs Canny Edge Detection on the Image
Calculates the Hough Transform values
Determines the peaks
Determines the deviation of each peaks from 45 degree angle
Segregates the detected peaks into bins
Chooses the probable skew angle using the value in the bins

The deskew script uses the skew angle determined using skew detection script to remove the skew from the image.

Using scripts directly(older method)

Image skew calculation using skew_detect.py

To calculate the skew angle for a given image file, use -i option followed by the path to file:

./skew_detect.py -i image.jpg

To save output in a text file add -o option followed by the output file name:

./skew_detect.py -i image.jpg -o output.txt

To display output information add -d option followed by a string Yes:

./skew_detect.py -i image.jpg -d Yes

To batch process files in a directory, use -b option followed by the path to directory:

./skew_detect.py  -b examples

To display Hough Transform plot for an image,:

./skew_detect.py -i image.jpg -p Yes

Output of the Hough Transform:

To set the value of sigma for Gaussian blurring in Canny Edge Detection, use -s option followed by the desired value:

./skew_detect.py -i image.jpg -s 3

To set the number of peaks collected from Hough Transform, use -n option followed by the desired value:

./skew_detect.py -i image.jpg -n 10

Image Deskew using deskew.py

To perform a simple deskew and display the output:

./deskew.py -i image.jpg -d Yes

To save the deskewed image, use the following:

./deskew.py -i image.jpg -o rotated.jpg

In some cases the result image might be upside down or the text may be running vertical, To fix this, use -r followed by the desired angle in int:

./deskew.py -i image.jpg -o rotated.jpg -r 90

To generate data for experimental purposes, run the test_img_gen.py in test_data folder. This will generate images containing a white line having angle between 0 to 180 degrees.

kakul / Alyn