We propose a framework that enables vision-based navigation systems to more robustly recognize signboards. It is designed mainly for signboards with uniform color regions, which can be strongly affected by occlusion and reflection. The framework comprises two stages: preprocessing for extracting uniform color regions and recognizing them. In the first stage, the cumulative frequency, morphology gradient, and Mahalanobis distance are used for the extraction. In the second stage, a new matching method for identifying templates and a new relative method for verifying colors are used. Testing of a system using this framework and 300 images taken under various conditions showed a recognition rate of 98%, demonstrating the framework's powerful ability to recognize signboards.