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This paper describes a background noise elimination technique introduced for License Plate (LP) detection algorithms specifically designed for High Definition (HD) images to deal with the surplus data they contain. The images are firstly enhanced using a robust method, followed by the application of morphological operators and histogram percentile autonomous thresholding for removing background noises keeping the resulting image grey. Finally, greyscale edge detection based segmentation is applied to extract the candidate regions of interest. Experiments on thousands of images show an improvement not only in LP detection in HD images, but also in edges processing time, which compensates for the additional time due to background noise elimination. The proposed algorithm is also tested on Standard Definition (SD) images where higher LP detection success is observed on SD images with complex background scenes.