How to find and process Internet Graphics for Classroom Use

Visual World One picture is worth a thousand words. A good picture is a worth a thousand pictures but a good picture requires processing to be fit for a given purpose

A lot of things can go wrong… bleak colours…low contrast…limited colours… blue tinge…

A lot of things can go wrong… … but a lot can be improved.

Overview of the workshop Find (an image) Optimize it Use it effectively

Real (reverse) overview A bit of theory Processing Search engines and software Tips and tricks

Theory – key concepts Pixel Resolution Compression Color depth Vector vs raster graphics File formats

Theory – pixel – 1 Pixels are building blocks of an image. Magnified image – pixels visible

Theory – pixel – 2 Information about each pixel in an image contains its detailed: position in the picture (where to put the given pixel) precise colour description (how to build colour of the pixel) An average postcard size photograph contains more than 2 million pixels (1600x1200); The more pixels a given area has the better quality of the image is

Theory – resolution – 1 The level of detail an image holds Unit: pixels/dots per inch Source: wikipedia.org 1 pixel per inch 2 pixels per inch 5 pixels per inch The more pixels per inch the clearer the image

Theory – resolution 2 72 ppi 18 ppi Resolution and quality

Theory – resolution – 3 Optimum resolution for computer screen is 96 ppi (presentation, web) Optimum resolution for computer printout is 150 ppi (home printer) Optimum resolution for professional printing is 300 ppi and up

Theory – compression Uncompressed high quality images take a lot of disk space (a single photograph about MB) The process of compression reduces the amount of data by eliminating lengthy descriptions of the pixels; one description is used for all identical pixels or eliminating the differences between pixels the eye wouldnt be able to see

Theory – compression – types Lossless : data compression algorithms that allow the exact original data to be reconstructed from the compressed data. Lossy : data compression, which does not allow the exact original data to be reconstructed from the compressed data.

Theory – colour depth Scientific experiments have shown that the number of colours we can see range as high as 10 million. Computers initially used 2, later 16, 256, and now use 16,7 mln colours. The number of colours influences file size colours 90 kB 7 colours 15 kB

Vector vs raster graphics Raster image – each point (pixel) of the image is described individually Vector image – the sequences of points are defined by mathematical formulas The red line is described by y=x formula

Vector vs raster graphics vector raster

Why is all that so important? Number of pixels, resolution, compression, colour depth, type of graphics (raster/vector) determine the size and the quality of an image and its suitability for a given purpose

File formats Uncompressed: bmp, tif Compressed (lossless): gif, png Compressed (lossy): jpg Vector: wmf, emf

File formats - characteristics Bmp – too big for comfortable use; retains, however, all the important information Gif – only up to 256 colors can be represented (good for simple geometrical shapes, text) Jpg – full color (excellent for photographs) Wmf – small but artificial looking

File formats - characteristics Bmp – too big for comfortable use; retains, however, all the important information Gif – only up to 256 colors can be represented (good for simple geometrical shapes, text) Jpg – full color (excellent for photographs) Wmf – small but artificial looking

Basic processing using Irfan View Rotation Cropping Resizing/resampling Controlling color depth Improving contrast and saturation Enhancing colors Batch processing

Where to look for good graphics Search engines Free stock photographs:

Software – free & commercial Irfanview (free) ( Paint NET (free) ( Photofiltre (free) ( GIMP (free) ( Adobe Photoshop (Adobe Elements) ( Corel Photopaint (

Powerpoint presentation – too big 1.Process graphics (size, resolution, colors) 2.Save as gif/jpg files 3.Insert into the presentation 4.Link graphics instead of embedding it into the presentation (older Office software Steps 1-3 – use capture

Dog image 1.Go to and type dog; set search parameterswww.google.com 2.Good quality photograph: go to Vector image: go to

Only a part of an image is needed 1.Run Irfanview 2.Select the area you want to keep 3.Press Ctrl-Y 4.Save or copy image to buffer

Too red, too pale, too dark 1.Run Irfanview 2.Press Shift+G (or go to Image/Enhance colors) 3.Change color balance 4.Save file

Dark areas to be removed 1.Run Paint NET 2.Click Magic wand or Lasso select 3.Cut the unwanted parts

Batch processing 1.Run Irfanview 2.Go to File/Batch conversion/rename 3.Set parameters and press Start

Removing background in Powerpoint 1.Paste the image into PP 2.Click the image 3.In the image toolbar select Make area transparent

Web browser – saving protected images and flash images 1.Find the image 2.Press Print screen key 3.Run Irfanview 4.Paste the captured screen 5.Edit (crop?) and save

Thank you!