This paper proposes a method for detecting characters in grey-scale scene images for navigating vision-based mobile robot by character information. First, we extract subregions with high spatial frequency and great variance in grey-level from an input scene image as candidates of character components. Then, we select characters by using several heuristic such as constraints of size and shape, bimodality of an intensity histogram, alignment and proximity of characters. We conducted an experiment using 20 indoor and 40 outdoor images. As a result, character lines are detected with a high rate of 80
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