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Digital Ink Compression via Functional Approximation

机译:通过功能逼近进行数字墨水压缩

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Representing digital ink traces as points in a function space has proven useful for online recognition. Ink trace coordinates or their integral invariants are written as parametric functions and approximated by truncated orthogonal series. This representation captures the shape of the ink traces with a small number of coefficients in a form quite compact and independent of device resolution, and various geometric techniques may be employed for recognition. The simplicity and high performance of this method lead us to ask whether the same idea can be applied to another important aspect in online handwriting ȁ3; the compression of digital ink strokes. We have investigated Chebyshev, Legendre and Legendre-Sobolev orthogonal polynomial bases as well as Fourier series and have found that Chebyshev representation is the most suitable apparatus for compressing digital curves. We obtain compression rates of 30* to 50* and have the added benefit that the Legendre- Sobolev form, used for recognition, may be obtained by a single linear transformation.
机译:将数字墨水迹线表示为功能空间中的点已证明对于在线识别很有用。墨迹坐标或它们的整数不变量被写为参数函数,并通过截断的正交序列进行近似。该表示以非常紧凑的形式并独立于设备分辨率来捕获具有少量系数的墨水迹线的形状,并且可以采用各种几何技术进行识别。这种方法的简单性和高性能使我们开始质疑是否可以将相同的思想应用于在线手写的另一个重要方面aspect3;数字墨水笔触的压缩。我们研究了Chebyshev,Legendre和Legendre-Sobolev正交多项式基以及Fourier级数,并发现Chebyshev表示法是最适合压缩数字曲线的设备。我们获得30 *到50 *的压缩率,并具有额外的好处,即可以通过单个线性变换获得用于识别的Legendre-Sobolev形式。

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