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Statistical characteristics in HSI color model and position histogram based vehicle license plate detection

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Abstract

Visual perception takes an important role in the implementation of intelligent robot and transportation systems. Such perception is to detect and recognize various objects in the real environment. Detecting license plate (LP) is a crucial and inevitable component of the vehicle license plate recognition (VLPR) system. In this proposed algorithm, initially, HSI color model is adopted to select automatically statistical threshold value for detecting 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 character by using position histogram to verify and detect vehicle license plate (VLP) region. In experiment more than 150 images were used, and they were taken from the variety of conditions such as complex scenes, illumination changing, distances and varied weather etc. Under these conditions, success of LP detection has reached more than 94%.

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Correspondence to Kang-Hyun Jo.

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Deb, K., Kang, SJ. & Jo, KH. Statistical characteristics in HSI color model and position histogram based vehicle license plate detection. Intel Serv Robotics 2, 173–186 (2009). https://doi.org/10.1007/s11370-009-0043-x

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  • DOI: https://doi.org/10.1007/s11370-009-0043-x

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