A Framework for Traffic Sign Detection Based on Fuzzy Image Processing and Hu Features

The Traffic Sign Recognition (TSR) system is an essential part of traffic management, being support system for driver and intelligent vehicle. Traffic Sign Detection (TSD) is the prerequisite step of the automatic TSR system. This paper proposes a TSD framework by exploring fuzzy image processing and invariant geometric moments. In this framework, fuzzy inference system is applied to convert the HSV image into gray tone. Then, statistical threshold is used for the segmentation. After shape verification of every connected component using Hu moments and Quadratic Discriminant Analysis (QDA) model, the candidate signs are detected by referencing bounding box parameters. The framework is simulated in different complex scenarios of day and night mode. Experimental result shows that its performance is satisfactory and recommendable with the state of the art research. The proposed framework yields 94.86% F-measure in case of Bangladesh road signs and 93.01% in German road signs.