Vehicle license plate extraction based on color and geometrical features

Vehicle license plate recognition (VLPR) is one of the most important topics of using computer vision and pattern recognition in intelligent transportation systems. In order to recognize a license plate (LP) efficiently, the location of the LP in most cases must be extracted in the initial step. In this proposed algorithm, initially, HSI color model is adopted to select automatically statistical threshold value for extracting candidate regions. According to different colored LP, these candidate regions may include LP regions; geometrical properties of LP are then used for classification. The proposed method is able to deal with candidate regions under independent orientation and scale of the plate. Finally, the decomposition of candidate regions contains predetermined LP alphanumeric characters by using position in the histogram to verify and extract vehicle license plate (VLP) region. Experimental results show that the proposed method is very effective in coping with different images under the variety of conditions such as complex scenes, illumination changing, distances and varied weather etc.