【摘要】：自動車牌識別是智能交通系統(tǒng)中的重要模塊,一般包括車牌區(qū)域提取、車牌字符分割、車牌字符識別等處理步驟。由于受光照不均、字符陰影、背景紋理等干擾的影響,字符分割和識別的精度較低。因此,本文提出車牌字符分割及其預處理技術研究的課題,開展該項研究對提高車牌自動識別系統(tǒng)的精確性和魯棒性有重要的應用價值。本文主要工作和貢獻如下:基于車牌區(qū)域垂直邊緣高密度、邊緣點鄰域灰度對相似等特點,提出了一種抗背景區(qū)域干擾的車牌水平校正算法。首先,通過垂直邊緣密度濾波、近鄰垂直邊緣水平連接,得到車牌區(qū)域塊,并根據(jù)字符高度一致性以及位置的漸變性,提取有效的字符列,然后,利用最小二乘法基于所有字符列中點擬合直線,估計出車牌區(qū)域傾斜角。基于車牌底顏色模式種類固定、字符筆畫寬度一致的性質,提出了抗光照變化和背景紋理干擾的車牌顏色模式判斷算法。通過分析車牌區(qū)域可能出現(xiàn)的顏色并利用字符寬度一致性的特點,對色彩飽和度高和飽和度低的車牌分別使用顏色量化直方圖和形態(tài)學處理的方法來判斷。基于車牌區(qū)域字符面積比例固定和顏色一致等特點,構建了一種自適應的車牌二值化方法。首先,計算Otsu全局閾值,基于光照的平滑變化,通過與Bernsen局部閾值的加權,得到灰度接近全局閾值的像素的閾值,來克服光照不均的影響,再通過前景所占比例判斷是否需要選用基于RGB顏色空間的k-means聚類方法來區(qū)分字符陰影或非車牌區(qū)域、車牌背景和字符區(qū)域。基于車牌底色一致和字符排列方式固定等特點,提出了一種抗背景區(qū)域干擾的水平車牌字符分割方法。首先,對車牌二值圖垂直投影進行波谷分析,利用車牌底色的一致性估計左右邊界,并找到第二、第三個字符之間的間隔位置,為模板匹配提供參考位置;設計變長模板,在垂直投影直方圖上滑動,結合波谷約束以最大類間方差準則找到最佳匹配參數(shù),最后依據(jù)投影和字符寬度一致性進行分割位置的精確調整。最后,設計了本文算法的仿真實驗。對于現(xiàn)有700幅車牌圖像的數(shù)據(jù)集(包含無干擾和有光照影響、圖像背景區(qū)域干擾的圖像),分割準確率達到了97.28%,表明本文提出算法具有較好的適應性。
[Abstract]:Automatic license plate recognition is an important module in intelligent transportation system, which generally includes the processing steps of license plate region extraction, license plate character segmentation, license plate character recognition and so on. The accuracy of character segmentation and recognition is low due to the influence of uneven illumination, shadow of characters, background texture and so on. Therefore, this paper puts forward the research topic of license plate character segmentation and its preprocessing technology, which has important application value to improve the accuracy and robustness of license plate automatic recognition system. The main work and contributions of this paper are as follows: based on the high density of vertical edge of license plate area and the similarity of adjacent gray pairs of edge points, a license plate level correction algorithm against background interference is proposed. First, through vertical edge density filtering, the nearest vertical edge is connected horizontally, and the license plate area block is obtained. According to the character height consistency and the gradual change of position, the effective character column is extracted. The least-square method is used to estimate the inclination angle of license plate area by fitting straight lines based on the midpoints of all character columns. Based on the fixed color pattern at the bottom of the license plate and the uniform width of the character stroke, an algorithm for judging the color pattern of the license plate is proposed, which can resist the interference of illumination and background texture. By analyzing the possible colors in the license plate area and using the characteristics of character width consistency, the color quantization histogram and morphological processing are used to judge the license plate with high color saturation and low saturation respectively. Based on the characteristics of fixed area and uniform color in the license plate area, an adaptive binarization method of license plate is proposed. First of all, the global threshold of Otsu is calculated. Based on the smooth change of illumination, the threshold of pixels with gray level approaching global threshold is obtained by weighting with local threshold of Bernsen to overcome the influence of uneven illumination. Then the proportion of foreground is used to determine whether it is necessary to choose k-means clustering method based on RGB color space to distinguish character shadow or non-license plate region, license plate background and character region. Based on the characteristics of uniform background color and fixed character arrangement, a method of horizontal license plate character segmentation against background interference is proposed. Firstly, the vertical projection of the binary image of the license plate is analyzed, and the left and right boundary is estimated by the consistency of the bottom color of the license plate, and the interval between the second and the third characters is found to provide the reference position for template matching. The variable length template is designed to slide on the vertical projection histogram and the maximum inter-class variance criterion is used to find the best matching parameter combined with the trough constraint. Finally the segmentation position is accurately adjusted according to the consistency of projection and character width. Finally, the simulation experiment of this algorithm is designed. For the existing data sets of 700 license plate images (including images with no interference, illumination, background area interference), the segmentation accuracy reaches 97.28, which shows that the proposed algorithm has good adaptability.
【學位授予單位】：華中科技大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.41

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