Abstract
Most of the image retrieval systems published and implemented have focused on basic features like color, shape and texture of an image with little or no consideration of the included text region of the image. In this work, we have developed an image retrieval system that works on finding similar composite images containing graphical shapes as well as text from a database of thousands of images. By proposing a novel method for text localization, extraction followed by detection, we have demonstrated how this method outperforms commercial OCR tools. The significant feature of this work is its handling the requirements of invariance to font size, design, text region orientation and its ability to give accurate result even in the presence of complex background and graphical elements. The methodology has been tested for English text but is capable to handle any other language.
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