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This paper presents a comparative study of improvements to the algorithms for license plate extraction from images captured using conventional, modest-quality cameras. It compares the results and efficacy of two similar algorithms which primarily differ in the raw image pre-processing stage of the initial image. One algorithm uses the Gabor filter bank with distinctly crisp parameters; the other relies on the fuzzified Gabor filter bank with fuzzified parameters to facilitate their adjustment. Results indicate that the fuzzy reasoning introduced for Gabor filter parameter adjustment improves the detection of the components of interest in complex images and adds minimal deviation compared to the Gabor filter bank with distinctly crisp parameters.

Comparison of Gabor Filter Bank and Fuzzified Gabor Filter for License Plate Detection