A new split-and-merge technique for polygonal approximation of chain coded curves

Polygonal Approximation of Digital Curves Using the State-of-the-art Metaheuristics

“…An attempt using the dynamic programming technique had been made (Dunham, 1986), however, it required a worst-case complexity of O (N 4 ) where N is the number of data points. Early solutions to reduce the amount of computations rely on local search heuristics, namely the sequential scan-along approaches (Wall & Danielsson, 1984;Ray & Ray, 1993), split-and-merge approaches (Ansari & Delp, 1991;Ray & Ray, 1995), and dominant point detection approaches (Teh & Chin, 1989;Zhu & Chirlian, 1995). However, the quality of the approximation result depends upon the initial condition where the heuristics take place and the metric used to measure the curvature.…”

On-line segmentation of freehand sketches by knowledge-based nonlinear thresholding operations

“…For the past two decades, many curve segmentation techniques have been proposed, most of which use straight lines to approximate the edge pixels in an image [5][6][7][8][9]. Chen, Ventura and Wu [10] emphasised that the piecewise linear approximation of digital curves is scarcely useful for segmenting curves in a meaningful and compact form.…”

On the Detection of Visual Features from Digital Curves Using a Metaheuristic Approach

“…Ansari and Delp [11] proposed another technique which first uses Gaussian smoothing to smooth the boundary and then takes the maximal curvature points as break points to which the split-and-merge process is applied. Ray and Ray [12] proposed an orientation-invariant and scale-invariant method by introducing the use of ranks of points and the normalized distances. If a poor initial segmentation is used, the approximation results of the split-and-merge approaches maybe far from the optimal one.…”