A. Kolesnikov

Publications (6)0 Total impact

• Conference Proceeding: Fast algorithm for error-bounded compression of digital curves

  A. Kolesnikov
  [show abstract] [hide abstract]
  ABSTRACT: A fast algorithm for compression of digital curves with minimal bitrate for a given error-bound was considered. The algorithm includes polygonal approximation with quantization of the vector data and compression of the quantized data with arithmetic encoder An asymptotically optimal quantizer for vector data was constructed with a quantization step proportional to the given RMSE bound. The proposed algorithm has demonstrated good compression and time performance on large-size data. The algorithms can be used in real-time applications and adapted for on-line implementation.
  Image Processing (ICIP), 2010 17th IEEE International Conference on; 10/2010
• Conference Proceeding: Approximation of digitized curves with cubic Bézier splines

  A. Kolesnikov
  [show abstract] [hide abstract]
  ABSTRACT: In this paper we examine a problem of digitized curves approximation for raster graphics vectorization and develop an efficient implementation of a near-optimal Dynamic Programming algorithm for digitized curves approximation with cubic Bézier splines for a given distortion bound. For better fitting performance, we introduce the inflection points with relaxed constraint of tangent continuity. The proposed algorithm demonstrates superiority over the iterative breakpoint-insertion method in terms of segments number for a given distortion bound.
  Image Processing (ICIP), 2010 17th IEEE International Conference on; 10/2010
• Conference Proceeding: Minimum Description Length approximation of digital curves

  A. Kolesnikov
  [show abstract] [hide abstract]
  ABSTRACT: In this paper we have examined a problem of piecewise approximation of digital curves with a set of models. Each segment of the input curve was approximated by a function selected from a given set of functions (line segments, circular arcs, polynomials, splines, etc). Following the minimum description length principle, we have introduced a fast near-optimal algorithm for multi-model error-bounded approximation of digital curves. The algorithm was tested on a large-sized test data se and demonstrated a sufficient trade-off between time performance and efficiency of solutions. The processing time for the large-size test data is less than 1s.
  Image Processing (ICIP), 2009 16th IEEE International Conference on; 12/2009
• Source

  Available from: usf.edu

  Conference Proceeding: Constrained piecewise linear approximation of digital curves

  A. Kolesnikov
  [show abstract] [hide abstract]
  ABSTRACT: We have considered a problem of continuous piecewise linear approximation of the digital curves with a minimum number of the line segments. Fast sub-optimal algorithm for constrained piecewise linear approximation is suggested to construct continuous piecewise linear representation of the input curve for a given error bound. The proposed fast sub-optimal algorithm can be used in combination with reduced-search dynamic programming algorithm to get a practically optimal solution in a few iterations. The proposed algorithms have demonstrated both high efficiency and time performance.
  Pattern Recognition, 2008. ICPR 2008. 19th International Conference on; 01/2009
• Source

  Available from: usf.edu

  Conference Proceeding: An online polygonal approximation of digital signals and curves with Dynamic Programming algorithm

  A. Kolesnikov
  [show abstract] [hide abstract]
  ABSTRACT: A fast online algorithm was developed for polygonal approximation of signals and curves with a minimum number of line segments for a given constraint on the standard deviation of the approximation error. A continuous Dynamic Programming search with piecewise backtracking of the locally optimal solutions is performed in overlapping windows. The developed online algorithm can be used for polygonal approximation of data streams, time series, digital signals, curves, and trajectories.
  Pattern Recognition, 2008. ICPR 2008. 19th International Conference on; 01/2009
• Conference Proceeding: Fast algorithm for ISE-bounded polygonal approximation

  A. Kolesnikov
  [show abstract] [hide abstract]
  ABSTRACT: In this paper we consider a problem of optimal polygonal approximation with a minimum number of the line segments for a given constraint on the total distortion with L2 measure. A fast suboptimal algorithm for the problem is proposed. In order to improve the solution obtained, this algorithm can be used in combination with a Reduced-Search Dynamic Programming algorithm. The experiments with the large size vector data have demonstrated both high efficiency and high time performance of the proposed algorithms for the following practical applications: image vectorization and segmentation, vector maps simplification, vector data compression, digital shapes encoding, etc.
  Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on; 11/2008