Analysis on Text Detection and Extraction from Complex Background Images

Text detection and extraction from complex images play a major role in detecting vigorous and valued information. As the rapid growth of obtainable multimedia information and rising prerequisite for data, documentation, indexing and reclamation, many scholars, researchers and scientists have worked a lot on text detection and extraction from the images. The main aim of this work is to give a comparison analysis on the various techniques and methods that were used and applied to detect and extract the text from complex background images. This comparison analysis will help to pick the proper and suitable technique or the method for future purpose. Many applications of text identification and verification are found, such as picture indexing based on text, Image searching the Google based on Keyword, old and required document examination, Extraction of number from number plates of vehicles involved in crime, etc. Detecting and extracting the text from images or video is demanding due to unconventionality of textured background, varying font size, different style, resolution, blurring, position, viewing angle, and so on. Enormous techniques have already been developed for detecting and extracting text from the complex background image. All these methods are based on substantial situations. So the purpose of the work is to provide an analysis on the accuracy of widely used algorithms by scholars and researchers in detecting and extracting the text from complex images. In this paper, the results of various methods for extracting the text from the images have been analyzed vigorously and this comparison analysis work helps the researchers to ease out the time complexity they find in searching for the different combinational works.