International Journal of Computer Vision
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Visually Searching the Web for Content
IEEE MultiMedia
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Histograms with Quality Guarantees
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Illuminant and gamma comprehensive normalisation in log RGB space
Pattern Recognition Letters - Special issue: Colour image processing and analysis
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Road Signs Recognition Using a Dynamic Pixel Aggregation Technique in the HSV Color Space
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
Color Recognition in Outdoor Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Spectral gradients for color-based object recognition and indexing
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
Fuzzy rule classifier: Capability for generalization in wood color recognition
Engineering Applications of Artificial Intelligence
PPCA-based license plate detection algorithm
ACM SIGSOFT Software Engineering Notes
Real-time vehicle tracking mechanism with license plate recognition from road images
The Journal of Supercomputing
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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.