Computer Graphics and Image Processing
Polygonal approximation by the minimax method
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Cited by (115)
Polygonal approximation based on coarse-grained parallel genetic algorithm
2020, Journal of Visual Communication and Image RepresentationCitation Excerpt :2) Given the error bound, the aim is to obtain the polygon that has the minimum number of vertices, and to make the error between the original shape curve and the approximating polygon not exceed the tolerance of error. Over recent decades, numerous methods have been proposed to solve the two types of polygonal approximation problems, such as (1) Sequential method [1–7]; (2) Spilt method, merge method, and split-and-merge method [8–12]; (3) Dominant and angle detection method [13–25]; (4) Newton’s method [26]; (5) Iteration method [27]; (6) k-means method [28–29]; (7) Dynamic programming [30–33]; (8) Bio-inspired intelligent algorithms [34–39]. Among all these methods, Ray and Ray [2] propose to obtain the polygon of object curve through making the line segment maximize and meanwhile making the approximation error minimize.
On the use of graph parsing for recognition of isolated hand postures of Polish Sign Language
2010, Pattern RecognitionCitation Excerpt :At the end, a contour is approximated with a polygon. A procedure used for this aim is based on the minimax approach to a polygonal approximation [55]. In this approach, the approximating segments are determined by minimizing the maximum distance between a given set of points and the corresponding segments.
The equipartition of curves
2009, Computational Geometry: Theory and ApplicationsSketch-based modeling: A survey
2009, Computers and Graphics (Pergamon)Citation Excerpt :In the general case, a robust algorithm will place some bounds on the amount of error introduced by approximation, retaining few samples in flat regions and more in regions with lots of detail. The minimax method [30], for instance, minimizes the maximum distance of any point to the straight-line approximating line. There are rigorous computational geometry approaches [31] for tackling this problem, but they are intended to operate on positional information; with sketched input, there is additional temporal information that can be used to identify perceptually important points in a stroke, such as corners (gradual direction changes) and darts (abrupt changes).
A similarity-based leaf image retrieval scheme: Joining shape and venation features
2008, Computer Vision and Image UnderstandingDominant point detection by reverse polygonization of digital curves
2008, Image and Vision Computing