Fuzzy-based algorithm for color recognition of license plates

Color recognition of license plates plays an important role in a license plate recognition (LPR) system. But it can be a challenging task as the appearances of license plates are affected by various factors such as illumination, camera characteristics, etc. And the color features of license plates in different places may be quite different. To address these concerns, this paper presents an algorithm based on fuzzy logic. The HSV (hue, saturation and value) color space is employed to perform color feature extraction. Three components of the HSV space are firstly mapped to fuzzy sets according to different membership functions. The fuzzy classification function for color recognition is, then, described by the fusion of three weighted membership degrees. For adaptation of the proposed algorithm, we also present a learning algorithm to obtain the correlative parameters. On a DSP-based embedded LPR platform, comparisons were drawn with other classifiers within three sets of test images. Experimental results show that the proposed algorithm achieves higher classification accuracy and better adaptability.