License plate location based on Tophat transformation and text texture
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摘要: 针对车牌自动识别系统的应用场景越来越广泛,提出一种新的基于Tophat滤波和文字纹理特征的车牌定位算法.首先,利用形态学Tophat滤波抑制背景、消除不均匀光照,然后对图像进行二值化操作和连通域分析;其次,扫描图像得到区域的垂直投影图(VPM, Vertical Projection Map),对VPM进行离散余弦变换(DCT, Discrete Cosine Transformation),利用中低频描绘子重构VPM,重构后的VPM更为平滑,不受噪声影响,其波峰波谷数量、统计量更能描绘区域纹理的本质属性;最后,结合部分中低频描绘子和统计量组成描述区域纹理的模式向量,输入支持向量机归类.实验表明,算法适用于自然场景中的车牌定位问题,具有较强的适应性.Abstract: Because the scene where license plate recognition system is located in is more and more complicated, license plate location method should have better performance. A new license plate location method based on Tophat transformation and text texture was introduced. First, Tophat transformation was applied to restrain background and eliminate variant illumination of image, and then binary operator and connected component analysis were applied. Second, the VPM(vertical projection map) of image was transferred to frequency space by DCT(discrete cosine transformation). The low frequency coefficients were used to reconstruct VPM. The reconstructed VPM was smoother, so region texture could be described essentially the wave crests and troughs number, statistic of reconstructed VPM. Last, pattern vectors were made up of low frequency component of frequency descriptors and statistic of reconstructed VPM, and were classified into license plate regions and non-license plate regions by SVM(support vector machine). Experimental results show that the method has good performance even when image has low quality and license plate is located in complicated natural scene.
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Key words:
- license plate /
- morphology /
- textures /
- support vector machine
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