CSI Communications | December 2012 | 23CSI Communications | December 2012 | 23

Let’s have a look into one more capability of Python programming

- image processing. Being a powerful programming language

with easy syntax, and extensible to C++ or Java, it is suitable for

developing embedded applications. Image processing is extremely

important in Python Platform. With the help of Python modules

Numpy and Scipy, Python competes with other similar platforms

for image processing.

Python Imaging Library (PIL) is one of the popular libraries

used for image processing. PIL can be used to display image, create

thumbnails, resize, rotation, convert between fi le formats, contrast

enhancement, fi lter and apply other digital image processing

techniques etc. PIL supports image formats like PNG, JPEG, GIF,

TIFF, BMP etc. It also possesses powerful image processing and

graphics capabilities. To start with image processing fi rst we need to

download PIL and install in PC. PIL supports python version 2.1 to 2.7.

One of the most important classes in PIL is image module.

It contains an in-built function to perform operations like - load

images, save, change format of image, and create new images. If

your PC is ready with PIL, you can start your fi rst program using PIL.

Let us open an image of water lily in Python. For this you

need to import image class and can follow the command Img = Image.open(lily.jpg’). Make sure that your image and

Python code are in the same folder. otherwise you need to specify

the path of image fi le.

1 import Image ## to import Image class

2 Img = Image.open(‘lily.jpg’) ## to open image-lily.jpg

3 print Img.format, ## to print format,Img.size, Img.mode size mode

4 Img.show() ## to show image in your image viewer

Now you can see image in your default image viewer. Here, the

third line gives the format of image, size of image in pixels, and

mode of the image (that is RGB or CYMK etc.).

Now to rotate the image by an angle, the following command

can be used.1 Img.rotate(45).show() ## to rotate image

by 45 degreeTo convert and save a RGB image to greyscale, the following

command can be used.

1 import Image2 Img = Image.open(‘lily.jpg’).convert(‘L’)3 Img.save(‘lily_greyscale.jpeg’,”jpeg”)

We may come across some situation to resize images, or create

a thumbnail of some image. Let’s see how this can be done using

Python.

1 import Image2 Img = Image.open(‘lily.jpg’)3 Img.thumbnail((128,128))4 Img. save(‘lily_thumbnail.jpg’,”JPEG”)

lily_greyscale.jpg

To start with some image processing, let us make a ‘negative’ of

the image ‘lily’.

Practitioner Workbench

Umesh PDepartment of Computational Biology and Bioinformatics, University of Kerala

Programming.Learn (“Python”) »

Image Processing in Python

With the help of Python modules Numpy and Scipy, Python competes with other similar platforms for image processing.

Neg_lily.jpg

lily.jpg

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Please try the following code. (For this you need to import two

more libraries - ImageChops and ImageFilter)

1 import Image2 import ImageChops3 import ImageFilter4 Img = Image.open(‘lily.jpg’)5 ImgNeg_lily = ImageChops.invert(Img)6 ImgNeg_lily.save(‘Neg_lily.jpg’,”JPEG”)

Now let us see some more fi ltering techniques that can be done

by using Python in-built classes. For the following fi lters, fi rst

you need to import modules - Image, ImageChops, and ImageFilter as in the previous example. After opening the

image in python, by ‘Image. open’ method (line 4 in previous

example), we can use diff erent fi lters - BLUR fi lter, EMBOSS fi lter,

CONTOUR fi lter, Find Edges Filter etc.

***Use commands 1,2,3,4 in previous program here*** ImBlur = Img.fi lter(ImageFilter.BLUR)ImBlur.save(‘lily_BLUR.jpg’,”JPEG”)

***Use commands 1,2,3,4 in previous program here*** ImEmb = Img.fi lter(ImageFilter.EMBOSS)ImEmb.save(‘lily_EMBOSS.jpg’,”JPEG”)

***Use commands 1,2,3,4 in previous program here***

ImContour = Img.fi lter(ImageFilter.CONTOUR)ImContour.save(‘lily_CONTOUR.jpg’,”JPEG”)

***Use commands 1,2,3,4 in previous program here*** ImEdges = Img.fi lter(ImageFilter.FIND_EDGES)ImEdges = ImEdges.save(‘lily_FIND_EDGES.jpg’,”JPEG”)

‘lily.jpg’ after applying the CONTOUR fi lter

‘lily.jpg’ after applying the FIND EDGES fi lter

You can convert an image into array for doing further operations,

which can be used for applying mathematical techniques like

Fourier Transform; the following code can be used.

1 import Image2 import numpy3 import scipy4 pic = Image.open(“lotus.jpg”)5 array = numpy.asarray(pic)6 print array

In this issue, we had a bird’s eye view of digital image processing

using Python. There are many more exciting experiments that

you can do with the image processing using Python. The power

of Numpy and Scipy adds more advantages to image processing.

n

lily.jpg’ after applying the BLUR fi lter

‘lily.jpg’ after applying the EMBOSS fi lter