The purpose of this project is to use Linear Pixel Shuffling with the "fat" pixel technique to implement a lossy compression of a black and white image. The implementation will be done in Java, and will be suitable for running from an applet on the World Wide Web.
The shuffling algorithm is taken from [2]. The algorithm is based on a two-dimensional Fibonacci sequence.
References used in the above:
[1] Anderson, P.G., "Advances in Linear Pixel Shuffling", presented at the Conference on Fibonacci numbers and their applications, Pullman, Wa., July 1994.
[2] Anderson, P.G., "Linear Pixel Shuffling for Image Processing, an Introduction", The Journal of Electronic Imaging. April 1993, pp. 147-154.
e-mail: emk3594(at sign)cs.rit.edu
Committee:
e-mail: szybist(at sign)kodak.com
Orienting document images can be a valuable step in a document processing system. This capability eases the document preparation process, and allows other processing steps to expect images in a known orientation. This project addresses document image orientation by concentrating on the text appearing in the document.
This system will capture characters from a scanned document, and attempt to recognize the characters and their orientations. The recognition will be performed by Optical Character Recognition (OCR) Neural Networks (NNs). Several systems will be configured by training a variety of NNs. The relative performance of each configuration will be evaluated.
Dr. Anderson has been doing research work on LPS (Linear Pixel Shuffling) theory for many years and he would like to implement his theory to a LPS Image (Graphics) Format, including LPS compression algorithm which is implemented by Elaine Meadows.
In my project, the following specs will be implemented:
(1) An html file invokes a Java applet file that brings out an ImageViewer frame.
(2) From the ImageViewer frame, the user may choose to open a GIF image file as original file or LPS image file with desired percent image shown.
(3) The user may save the image as a regular GIF file or in the LPS file format.
(4) This converter (display) project is implemented in JAVA and HTML and is able to displayed on WWW.
(5) The LPS converter will handle bilevel, monochrome, and color images.
In the second set of experiments, the problem is to train N-2-N compression networks to learn patterns of bits such that input equals output. The pattern to be learned has just one of the N bits "on." It turns out that this is a difficult problem to train for large N. Instead, we experimented with two indirect approaches. The report concludes with a summary of results from these experiments.