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曲线矢量化中的背景去噪方法
Background denoising methods in vectorization of curves
【摘要】 测井曲线矢量化是把测井图纸扫描成数字图像,采用图像处理与识别的理论与技术,把 图像中的测井曲线自动转换成数字量。测井曲线矢量化中的一个重要问题是如何去除背景和噪声。 为此,提出了频域滤波,十字模板匹配,线形Hough变换,灰度投影以及线模板匹配方法,并对这些方 法做了一些比较。
【Abstract】 The well log is vectorized by scanning the well log into a digital image and converting the curves in the image into digital data using the theories and technologies of image processing and recognition. One of the most important problems in the vectorization is how to remove the background and noises in the image. For this reason, the methods of frequency domain filtering, cross templet matching, linear Hough transform, intensity projection, and line segment matching for background denoising were proposed. The merits of each method was compared to the others.
【关键词】 图像处理;
测井曲线矢量化;
背景去噪;
Hough变换;
模板匹配;
【Key words】 image processing; well log vectorization; background denoising; Hough transform; templet matching;
【Key words】 image processing; well log vectorization; background denoising; Hough transform; templet matching;
- 【文献出处】 计算机应用 ,Computer Applications , 编辑部邮箱 ,2005年04期
- 【分类号】TP391.41
- 【被引频次】14
- 【下载频次】220