Pattern localization in historical document images via template matching
Template matching is a classical and essential step in many pattern recognition, object detection or video tracking systems. This paper aims at integrating and evaluating different template matching methods in the context of pattern spotting in historical document images — i.e. the search for occurrences of a given visual pattern in document images. Given a query image, our pattern spotting system first computes the similarity score between the query signature and the signatures of a few regions provided by a region proposal algorithm. The top ranked regions are then selected for further processing. Template Matching is then applied in the neighborhood of the selected regions to precisely locate and rank the candidate windows that maximize the matching score. This paper builds upon popular template matching approaches and provides a unified testing framework for historical document image pattern spotting. The experimentation offers an insight on how to choose the most promising techniques for historical document images. This paper also proposes an improvement over these standard template matching approaches to significantly increase the overall performance.