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Image Vectorisation in Digital Image Watermarking

机译:在数字式图象水印的图像vectorisation

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Unlike most previous work, which used a random number of a sequence of bits or an image as watermark directly, this paper proposed a new image vectorisation method for digital image watermarking. A watermark image (image to be embedded) is firstly contourised into a sequence of contour curves by constructing a "vector" for each of the grey level values. In the contourisation process, a topology analysis method is applied for looking for local maxima, minima and saddle points to implement a topology table. It is well known that the volume of "vector" data from real image contourisation may be up to an order of magnitude greater than the raster representation. Therefore, a simplification method is adopted to analysis the great expansion of data, and to determine which contours it is necessary to preserve in a given image and which contours can be discarded in that image. With help of previously obtained the topology table, image is decomposed into a number of adjacent sub regions known as catchments basins, each of which typically surrounds of a local maximum or minimum and is defined by a contour which is referred to as a watershed or watershed boundary. Then the simplified contour points are embedded as watermark onto the cover image by using the well known spread spectrum technique. After the contour points are extracted from watermarked image, the watermark image is reconstructed by constructing the triangle mesh defined by the contour map and rendering it using conventional rendering method.
机译:不同于大多数以前的工作,其使用的比特的序列或作为水印直接的图像的一个随机数,本文提出了一种数字水印的新图像向量化方法。水印图像(图像要被嵌入)首先contourised成通过构建一个“载体”为每个灰阶值的轮廓曲线的序列。在contourisation过程中,适用于寻找局部最大值,最小值和鞍点来实现拓扑表的拓扑分析方法。众所周知,从真实图像contourisation“载体”的数据量可以达到幅度大于光栅表示的顺序。因此,简化方法采用以分析数据的极大扩张,并确定它是轮廓所需要的给定图像中保存和其轮廓可以在该图像中被丢弃。与先前得到的拓扑表的帮助下,图像被分解为若干称为集水盆,其中的每一个通常围绕一个局部最大或最小的并且是由被称为一个分水岭或流域的轮廓限定的相邻子区域的边界。然后简化轮廓点,通过使用公知的扩频技术嵌入作为水印到盖图像。轮廓点是从加水印的图像中提取后,水印图像是通过构造由轮廓映射中定义的三角形网格,并用常规着色方法使其重建。

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