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標題: 新的具曲線筆觸繪圖成像演算法
作者: 王宗銘 
關鍵字: 圖像矩;曲線筆觸;繪圖成像;邊界測定
出版社: 國立中興大學工學院;Airiti Press Inc.
Project: 興大工程學刊, Volume 16, Issue 1, Page(s) 65-75.
Non-photorealistic rendering is a popular research topic in computer graphics communities, where painterly rendering has recently been under intensive studies. Painterly rendering algorithms based on the image moment have demonstrated some success, pro-ducing visually plausible painting images. However, most of these algorithms employed line-based brush strokes, disregarding the curved-stokes natures that have been adopted by painters in the real world. In this paper, we present a novel curved-strokes algorithm based on the image moment for painterly rendering. First, our algorithm employs the line integral convolution technique to determine a curved line passing thorough pixels coincident with the gradients of the image. Second, along with visiting every pixel in the line, we calculate the magnitude of the image moment to determine whether a stroke is to be drawn on the pixel currently visited, Next, the sizes and directions of the stroke are automatically determined we first compare the variances of the image moment at the current pixel, with those of the images moment in the neighborhood pixels. We then determine suitable magnitude of sizes and directions through linear interpolation calculation. Under this mechanism, a stroke with a small size and short length will be assigened to a pixel with small magnitude of the image moment. Third, we apply an image segmentation technique to identify boundaries of objects. When proceeding to painterly rendering, we can make sure that strokes will all be maintained inside the objects, without passing through the boundaries. Finally, we use a Gaussian filter on the original image and replace those pixels that is not drawn by any strokes. This allows us to simulate painterly rendering images when considering the existence of the canvas. We demonstrate some painterly rendering images, and compare our images with those proposed in the literature. Experimental results verify that our algorithm performs far better than the previous algorithms.

ISSN: 1017-4397
Appears in Collections:第16卷 第1期

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