Designing a New Intelligent Image Processing Algorithm for Traffic Sign Detection and Recognition Based on Fuzzy Logic

A new algorithm for traffic sign detection and recognition based on image processing was presented in this paper. This algorithm has three stages that consist of preprocessing, detection and recognition. In preprocessing stage, input image quality enhancement and unrelated data elimination be done by applying image processing algorithms. In recognition stage an intelligent machine vision algorithm is used to extract concepts of traffic signs. Detection stage is designed for decrease the operation time and increase the recognition algorithm accuracy. In this stage, traffic sign candidates are elected more accurately and they are transmitted to recognition stage. Fuzzy logic and mathematics is used in all of image processing and machine vision stages that consist of low and high level processing. Also for traffic sign recognition, invariant features are used to design a fuzzy logic algorithm to extract traffic sign concepts. Fuzzy logic and mathematics give Inference and intelligent capabilities to smart system to make correct decision in actual conditions like human. All stages of this algorithm was implemented in MATLAB. Also for performance investigation of this algorithm experimental scenarios in actual situation are designed. The results show that designed algorithm has an appropriate performance in traffic sign detection and recognition up to 92.68 percent in actual situations. Compared with other methods with the same experimental conditions the accuracy of the proposed algorithm is satisfactory. This algorithm can be used to design driver assistance and control systems for intelligent vehicles.