A novel Web image processing algorithm for text area identification that helps commercial OCR engines to improve their Web image recognition efficiency

In this paper, a novel Web image processing algorithm is presented for text area identification. Statistics show that a significant part of Web text information is encoded in Web images. Since Web images have special characteristics that sometimes distinguish them from other types of images, commercial OCR products often fail to recognize Web images due to their special key characteristics. This paper proposes a novel Web image processing algorithm that aims to locate text areas and prepare them for OCR procedure with best results. According to this algorithm, first the Web color image is converted to gray scale in order to record the transitions of brightness that are perceived by the human eye. Then, an edge extraction technique facilitates the extraction of all objects as well as of all inverted objects. A conditional dilation technique applied with several iterations helps to choose text and inverted text objects among all objects. Experimental results, obtained from a large corpus of Web images, demonstrate the improvement in recognition accuracy after applying the proposed text area identification algorithm.