一种古建墙壁受污题记文字图像边缘提取方法

An Edge Extraction Method for Polluted Text Image of Ancient Inscription Wall

针对古建墙壁题记文字图像受污染影响而边缘提取不完整、易产生伪边缘和不连续边缘等问题,提出了一种受污题记文字边缘提取的方法。首先,对文字图像进行全变分去噪和多尺度视网膜算法明暗增强预处理;然后构造阴影-遮挡准不变模型滤除污染和背景产生的伪边缘,并用Gabor滤波器对其进行空间平均,建立颜色结构张量,结合Canny算法进行边缘提取;最后,通过形态学方法滤除图像中存在的小面积边缘,并做区域连通处理,得到题记文字边缘图像。实验结果表明,相比传统的Canny算法和Sobel算法,该方法有效地克服了污垢和背景造成的伪边缘和不连续边缘,很好地提取出了完整的题记文字边缘,在边缘品质EQ等客观指标上有较明显提升。

On the issue that inscription text image of the ancient wall is contaminated leading to its edge extraction is not complete, easy to produce false edge and discontinuous margin, this paper proposes a novel method of edge extraction from polluted inscription text. Firstly, text image for total variation denoising and multi-scale retinal algorithm shading to enhance preprocessing is used. Then construct a shadow-blocking quasi-invariant model filtering out pollution and pseudo-edge generated by background. Meanwhile, use Gabor filter to do spatial averaging and establish color structure tensor combined with Canny algorithm to do edge detection. Finally, filter small area edge existing in the image by morphological method and do the regional connectivity to obtain the edge inscription text image. The results show that, compared to traditional Canny algorithm and morphological method, this method effectively overcomes the false edge and discontinuous edge caused by dirt and background which makes good extraction of edge inscription from the full text and a more objective indicators such that edge quality has improved significantly.