In this work, we create artistic closed loop curves that trace out images and 3D shapes, which we then hide in musical audio as a form of steganography. We use traveling salesperson art to create artistic plane loops to trace out image contours, and we use Hamiltonian cycles on triangle meshes to create artistic space loops that fill out 3D surfaces. Our embedding scheme is designed to faithfully preserve the geometry of these loops after lossy compression, while keeping their presence undetectable to the audio listener. To accomplish this, we hide each dimension of the curve in a different frequency, and we perturb a sliding window sum of the magnitude of that frequency to best match the target curve at that dimension, while hiding scale information in that frequency's phase. In the process, we exploit geometric properties of the curves to help to more effectively hide and recover them. Our scheme is simple and encoding happens efficiently with a nonnegative least squares framework, while decoding is trivial. We validate our technique quantitatively on large datasets of images and audio, and we show results of a crowd sourced listening test that validate that the hidden information is indeed unobtrusive.
翻译:在这项工作中,我们创建了艺术封闭循环曲线,以追踪图像和3D形状,然后将其隐藏在音乐音频中,作为摄像学的一种形式。我们使用巡回销售员艺术,以创建艺术平流环以追踪图像轮廓,我们在三角间环状上使用汉密尔顿周期来创建艺术空间环状,以填充3D表面。我们的嵌入计划旨在忠实保存这些环状的几何结构,在丢失压缩后,同时将其存在不为听音者所察觉。要做到这一点,我们以不同频率隐藏曲线的每个维度,我们用这种频度的滑动窗口总和该频度最符合目标曲线的尺寸,同时在三角间段阶段隐藏比例信息。在这个过程中,我们利用曲线的几何特性来帮助更有效地隐藏和回收3D表面。我们的计划很简单,并且编译过程效率很高,同时不为听音频和音频大数据设置的解码框架。我们验证了我们的技术,在数量上对图像和音频的大小数据设置进行定量验证,我们展示了隐藏源测试的结果。