dc.description.abstract | This paper presents an approach for license plate recognition using a camera-equipped smartphone. The proposed method provides a reliable and accurate technique to solve the problem of license plate recognition caused by the skew and shadow on the license plates. There are four stages in the proposed approach: license plate location, license plate rectification, character segmentation and character recognition.
In the first stage, we locate the license plate by accumulating edge points, and then analyze the edge points and accumulation associated with vertical and horizontal dimensions of the image. As to the second stage, license plate rectification, we adopt local threshold to cope with the problem of shadow on the plates first. Next step involved analyzing black and white pixels in order to decide whether to invert the image or not. The researcher tries to engage the characteristics like length-width ratio, size, and position of the bounding box in the text region to eliminate the non-text portions. To solve the rotation, skew, and scale problems of the slanted license plates in the image, we use an affine transformation to estimate the skew angle.
Edge points vertical direction accumulating and trough are used to segment characters section in the third stage. We normalize the characters size to 40 × 90. Finally, criterion of normalized cross-correlation is used in the last stage for character recognition. In behalf of shortening the process time for identification, the procedure of character reorganization is improved. We shrink the samples to one-fourth the size to conduct the first identification process. Then, three highest-coefficient samples are chosen to match the original input pattern. From these three samples, the highest-coefficient one is selected as the final result.
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