License Plate Recognition from Low-Quality Videos

This paper presents a novel hybrid method for extracting license plates and recognizing characters from low-quality videos using morphological operations and Adaboost algorithm. First of all, the hybrid method uses the Adaboost algorithm for training a detector to detect license plates. This algorithm works well to detect license plates having lower intensities but fails to detect license plates if they are skewed. Thus, we use a morphology-based scheme to detect inclined license plates. The morphology-based scheme extracts important contrast features for searching possible license plate candidates. The contrast feature is robust to lighting changes and invariant to different transformations. The hybrid method can avoid the significant growth of training samples for training the detector to detect any oriented license plates. Then, a new segmentation method is proposed for character segmentation and recognition. Even though lower-quality video frames are handed, our method still perfo...

• Type: Conference
• Year: 2007
• Where: MVA
• Authors: Chih-Chiang Chen, Jun-Wei Hsieh
• Keywords: Computer Vision, Hybrid Method, Inclined License Plates, License Plate, MVA 2007