TJHSST Computer Systems Lab Senior
Reasearch Project
Dynamic Image Resizing
Quarter 2 Paper
Patrick Elliott
January 21, 2008
1 Abstract
The goal of this project is to be able to resize an image without distorting
any important aspects of the image. Commons methods of resizing, including
cropping and scaling, remove or distort some of the image and are thus
undesirable. By finding the least important pixels and removing them, this
dynamic resizing can be possible. These can be found by finding the change
of intensity of each pixel to the next and taking away the ones with a very
low change. Using this method, humans should be unable to tell if an image
has been altered.
2 Introduction
Currently on the web, there is such a thing as dynamic text formatting. For
instance, when you resize a web browser window, the text in it will adjust
itself to fit inside the window while still being readable. There is nothing
like this for images however. My goal in this project is to be able to change
the dimensions of an image without losing important content, such as the
dimensions of the focus of these pictures.
1
3 Background
Edge detection is being researched heavily in modern times. Many teams
are trying to allow computers to see and identify objects. But there is also
much research being conducted about images and modifying them. There
is one project called PhotoSynth that is trying to take a large amount of
images from the web, and from them, create a 3D model of whatever the
images are of. There is also another project that is very similar to what I
am trying to do, although I have some ideas for my project that they have
not yet implemented.
4 Development
I will be using C for all of my programming. In order to resize the images, the
program will first convert the image to grayscale by averaging the red, green
and blue values for every pixel. In order to find the least important pixels
(the ones that should be removed to harm the image the least), the gradient
magnitude function will be placed on the image. What this fun