Multi-thresholding Character Extraction in a Map

Abstract

Maps provide many pieces of information such as countries, cities, rivers, etc, which are useful to human beings in a geographic information system(GIS). This paper aims to extract the information automatically from a map to build a data base for user retrival. Character extraction and recongnition is one of the essential tasks for entering the map information into a computer. Because the input to the system is a grayscale map, we propose a method to extract Chinese characters in the map via the wulti-thresholding scheme in two phases. In the first phase, we extract the Chinese characters from a map, which is represented by multi-level values. After performing binarization, the character extraction operations containing three processes, named blurring, connected component extraction and rotation angle detection are conducted repeatively based on dufferent thresholds. After characters are extracted from the map, they are sent to a statistical-based character recognition module and substracted from the map. In the second phase, we extract simple components from the remained map by the runlength method to remove long components, which may be road lines. Then character extraction operations used in the first phase are performed again to extract characters. These extracted characters are also sent to the recognition module. The extraction rate for the testing maps in our system in over82%.