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Digital Ink Compression via Functional Approximation

机译:通过功能近似数字墨水压缩

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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 – 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:作为函数空间中的点代表数字墨水迹线已被证明可用于在线识别。墨迹跟踪坐标或其积分不变性被写为参数函数并由截断正交系列近似。该表示捕获具有少量系数的墨迹迹线的形状,其形式非常紧凑并且独立于设备分辨率,并且可以采用各种几何技术来识别。这种方法的简单性和高性能导致我们询问相同的想法是否可以应用于在线手写中的另一个重要方面 - 数字墨水冲程的压缩。我们研究了Chebyshev,Legendre和Legendre-Sobolev正交多项式基础以及傅立叶系列,并发现Chebyshev表示是压缩数字曲线的最合适的装置。我们获得了30 *至50 *的压缩率,并且具有用于识别的传奇文化形式的附加好处可以通过单个线性变换来获得。

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