With digital technology becoming cheaper and less specialised, the techniques investigated here may become integrated into computationally intelligent mobile phone devices. Such devices could be used to check documents quickly and efficiently.
The key to the technique was the production of a skeleton of text characters from their digitally captured image. A skeleton is a line defined by a binary (0,1) value. The location of the binary line defines the edges of the text character from which accurate length measurements of the text character can be automatically taken. An algorithm processes the data to produce a shape factor. The computer then recognises a text character with a particular font by comparing its shape factor with the shape factors from different text characters in its database. The algorithm was developed solely by the author to carry out this task. The results of the research were that small differences in fonts could be detected by high resolution digital image analysis, and be used to objectively quantify small differences in font style.
Conference papers were selected and subjected to review by the editor and the conference program committee. They comprise electronic imaging and cognitive research specialists from international universities, and commercial organisations.
|Type of Research:||Conference, Symposium or Workshop Item (Paper)|
|Keywords/subjects not otherwise listed:||RAE2008 UoA63|
|Your affiliations with UAL:||Colleges > London College of Communication|
|Date:||01 June 2003|
|Deposited By:||INVALID USER|
|Deposited On:||03 Dec 2009 23:56|
|Last Modified:||03 May 2011 11:10|