摘要： 边缘检测和图像分割算法直接应用于壁画线描画提取时,对一条笔道通常会产生2次响应,且其结果一般为单像素宽度,无法生成定位准确并同时保留壁画原有风格的笔道。针对该问题,提出一种结合灰度信息和边缘信息的壁画线描画生成方法。使用基于高斯模糊的高频提升滤波,简化壁画背景像素灰度值的分布,利用阈值分割和边缘检测算法提取笔道,并进行叠加,以生成完整线描画,通过矢量化,使笔道边缘更光滑。实验结果表明,当壁画笔道的灰度值小于其周围背景的灰度值时,与Canny算子和gPb算子等边缘检测方法相比,该方法能准确定位笔道,且提取的笔道具有一定的宽度,能够反映壁画的原有风格。
关键词:
线描画,
高斯模糊,
高频提升滤波,
阈值分割,
矢量化
Abstract: When edge detection and image segmentation are directly applied to the extraction of mural strokes,they usually generate two responses to a stroke,and the strokes in their results are generally a single pixel wide,unable to not obtain strokes with accurate location and original mural style.In order to solve this problem,a method combining grayscale information with edge information is proposed.A Gaussian blur based high frequency improvement filtering is used to simplify the histogram of the image’s background.Strokes which are extracted by threshold segmentation and edge detection separately are integrated to obtain the complete line drawing.Vector quantization is provided to make the stroke’s edge smooth.Experimental results indicate that when the gray value of strokes is less than that of background around strokes,compared with Canny detector,gPb detector, and other edge detection methods,the proposed method can locate strokes accurately,and strokes have a certain width,which can reflect the original mural style.
Key words:
line drawing,
Gaussian blur,
high frequency improvement filtering,
threshold segmentation,
vector quantization
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