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Detection and tracking strategy for license plate detection in video
Authors:Runmin Wang  Nong Sang  Ruolin Wang  Liangwei Jiang
Institution:1. Science and Technology on Multi-spectral Information Processing Laboratory, School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China;2. School of Civil Engineering, Wuhan University, Wuhan 430072, China
Abstract:In this paper, we present a novel method to detect license plates in video sequences automatically. The framework mainly integrates the cascade detectors method and the Tracking Learning Detection (TLD) algorithm. The cascade detectors are used to detect license plates, and the TLD algorithm is adopted to track the license plate regions. The license plates in the first frame image are detected by the cascade detectors to build the original tracking list, the tracking results and the detection results in following frames will be compared, and the newly appearing license plate information will be added to the tracking list. Meanwhile, the tracking results existing in the current tracking list would be replaced by the corresponding detection results with higher degree of confidence. We demonstrate the effectiveness of our algorithm for license plate detection task on a road intersection dataset, and the experimental evaluation shows the detection performance has been greatly improved by synthetically using the detection and tracking strategy.
Keywords:License plate detection  Cascade detectors  HOG classifier  TLD
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