Compression of image contours using combinatorial optimization

Compression of image contours is an important problem in many contexts. An example is object oriented video coding, where efficient encoding of shape information of arbitrarily shaped objects is a major problem. This paper presents a method for compressing contours by extracting representative points from the original curve. By formulating the point selection problem as a graph theory problem, known optimization theory can be applied in order to yield optimal compression with respect to a given error bound. The contour is reconstructed based on linear interpolation among the extracted curve points. The method presented guarantees a minimal distortion for a given number of retained curve points. Compared to many other compression methods, this method shows superior performance.

[1]  Aggelos K. Katsaggelos,et al.  An efficient boundary encoding scheme which is optimal in the rate distortion sense , 1997, Proceedings of International Conference on Image Processing.

[2]  J. G. Heber,et al.  An efficient implementation of an optimal time domain ECG coder , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  Aggelos K. Katsaggelos,et al.  An Optimal Polygonal Boundary Encoding Scheme , 1997 .

[4]  Dag Haugland,et al.  Compressing ECG signals by piecewise polynomial approximation , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[5]  Isabel Beichl,et al.  A simple algorithm for efficient piecewise linear approximation of space curves , 1997, Proceedings of International Conference on Image Processing.