Recognition of Road Names in Maps

• Main Authors: Tsai, Chun-Ming, 蔡俊明
• Other Authors: Hsi-Jian Lee
• Format: Others
• Language: zh-TW
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/91448732934427171752

碩士 === 國立交通大學 === 資訊工程學系 === 84 === This thesis presents a system to identify road names from a map. A map consists of a large number of entities, such as geographic landmarks, cities, rivers, roads, grid lines, country borders, institution names, and city borders. Road names often distribute nonuniformly in a map. They may rotate, vary in size or font type, touch lines or touch each other seriously. These problems make character extraction and recognition of road names very difficult. This thesis presents some methods to solve these problems. We first propose a connected-component-based method to extract the index table and its characters. The operations include binarization, connected component analysis, rules checking, and understanding. Second, we propose an cascade OCR system to recognize the characters of the index table. The characters include Ming font, multi-size Chinese characters, English characters and numerals in a map. In this OCR system, statistical and structural features are used to recognize characters. This system consists of four phases: preprocessing, feature extraction, classification, and postprocessing. The preprocessing phase performs thresholding and masking. In the feature extraction phase, we compute four types of features, which are Walsh transformation, pixel distributions, crossing counts, and long horizontal-vertical strokes. In classification phase, preclassification and cascade fine matching are performed. Three kinds of features are used serially in the fine matching. In the final postprocessing phase, candidates outputted from the fine matching module are tuned according to the frequency rate trained from characters collected from a tour book. At last, the top two candidates with the highest scores are chosen as the recognition results. In the last part, a geometry-based algorithm is proposed to identify the road names of the index table. This algorithm includes road line extension, shortest distance coincidence, rules checking, and some constraint satisfaction. The testing maps of our experiments contain nine maps. All index tables and characters in the index tables can be extracted. The recognition rate of characters in index tables is 98.23%, and the identification rate of road names is 95.54%. These experimental results show that the proposed system is rather effective.