IMPLEMENTATION OF BPCS-STEGANOGRAPHY

Implementation of BPCS-Steganography

      Abstract

                   Automatic identification of handwritten script facilitates many important. Applications such as automatic transcription of multilingual documents and search for documents on the Web containing a particular script. The increase in usage of handheld devices which accept handwritten input has created a growing demand for algorithms that can efficiently analyze and retrieve handwritten data. This project proposes a method to classify words and lines in an online handwritten document into one of the six major scripts: Arabic, Cyrillic, Devnagari, Han, Hebrew, or Roman. The classification is based on 11 different spatial and temporal features extracted from the strokes of the words. The proposed system attains an overall

 Classification accuracy of 87.1 percent at the word level with 5-fold cross validation on a data set containing 13,379 words. The classification accuracy improves to 95 percent as the number of words in the test sample is increased to five, and to 95.5 percent for complete text lines consisting of an average of seven words.

 

             Hardware Specification

Monitor                 :       14” color

Mother Board        :         Intel 810E chip set

Processor               :         Pentium Celeron

Processor Speed    :       850 MHZ

Memory Size         :         128MB

Hard Disk Drive    :         40GB

CD Drive               :      52 X

Floppy Drive         :         1.44 Floppy Drives

Keyboard              :          104 keys

Mouse                   :          Scroll Mouse

Display Card         :         VGA

Software Specification

Operating System            :       Windows 98/2000/NT

Front End                         :      JAVA 2.0

Back End                         :       ORACLE 8i