Devanagari text extraction from natural scene images

In scenic images, information in the form of text provides vital clues for most applications based on image processing. These include assisted navigation content based image retrieval, automatic geocoding and understanding the scene. But in a multicolored complex background, it is quite a daunting task to locate the text. This task is daunting because of non-uniformity in illumination, complexity of the backdrop, and differences in the size font & line-orientation of the text. We propose a novel approach for Devanagari text extraction from natural scene images in this paper. We can use a text-to-speech engine or Optical Character Reader to recognize the extracted text. The basis of our scheme is to analyze the CCs. This is done to extract Devanagari text from scenic images captured by camera. The presence of head line is unique to this script. Our scheme makes use of mathematical morphological operations to extract the headlines. Also the binarization of scenic images was studied. Here the effectiveness of the adaptive thresholding approach was observed. The algorithm was tested on Devanagari text contained within a collection of 100 scenic images.