Text image matching without language model using a Hausdorff distance

In this paper, we propose a text matching method for document image retrieval without any language model. Two word images are first normalized to an appropriate size and image features are extracted using the local crowdedness method. Similarity between the two features is then measured by calculating a Hausdorff distance. We performed three experiments. The first experiment proves the effectiveness of the proposed method for text matching, and the other two experiments verify the language independence and font size independence of the proposed method.