Text Localization & Extraction using PSO & BFO Techniques

Abstract

Text objects occurring in image documents can provide much useful information for content based information retrieval and counting applications, because they contain much Collins information related to the documents contents. However, extracting text from images and videos is a very difficult task due to the varying font, size, color, orientation, and malformation of text objects. Although a large number of text extraction approaches have been reported in the past work, no specific designed text model and character features are presented to capture the unique properties and structure of characters and text objects. We have proposed BFO & PSO Techniques in our research. The thesis primarily was focused on the design of an algorithm to extract the text from images and it’s implementation on MATLAB.