An efficient technique for capturing 2D objects

Masood, Asif; Sarfraz, Muhammad

doi:10.1016/j.cag.2007.10.002

Cited by 9 publications

(5 citation statements)

References 35 publications

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“…13d, the approximation is shown with algorithm. 37 It consists of 81 control points. Both the maximum error and average error are higher with values of 2.21 and 1.38, respectively.…”

Section: Results Analysis and Comparative Studymentioning

confidence: 99%

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Optimal curve fitting approach to represent outlines of 2D shapes

Masood¹,

Ejaz²

2010

The Imaging Science Journal

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A new outline capturing system is presented in this paper. It employs Bezier curve for curve approximation. Approximation starts with an initial estimation of control points positions, which is updated iteratively based on computed error. Consequently, the control points converge to an optimum position. The segments obtained after corner detection are initially approximated with Bezier curve of lowest degree, i.e. degree 1. The degree of approximating curve is then increased iteratively until the error comes under the user specified limit. This ensures optimal fit with least number of control points. Shape representation results of proposed algorithm are compared with existing techniques. Experimental results show that proposed algorithm can approximate the 2D shapes with considerably less number of control points, when compared with existing techniques. Computational efficiency is another advantage of proposed algorithm. Presented algorithm can have very useful applications in CAD/CAGD and real-time computer vision algorithms.

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“…13d, the approximation is shown with algorithm. 37 It consists of 81 control points. Both the maximum error and average error are higher with values of 2.21 and 1.38, respectively.…”

Section: Results Analysis and Comparative Studymentioning

confidence: 99%

“…A variety of corner detection algorithms are available in the literature. 16,24,36,37 An algorithm by Sarfraz et al 35 is selected for its accuracy and efficiency. Summary of algorithm 35 is given below.…”

Section: Boundary Segmentationmentioning

confidence: 99%

Optimal curve fitting approach to represent outlines of 2D shapes

Masood¹,

Ejaz²

2010

The Imaging Science Journal

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“…Paper [10] describes solving the optimal approximation task via exhaustive search. Masood et al [11] and Kolesnikov [12] suggest more practical near-optimal algorithms with some heuristics including detection of corners and inflection points.…”

Section: Related Workmentioning

confidence: 99%

“…5 illustrates some principles which are used in contour tracing. At first, we do polygonal approximation of initial contour polygon instead of fitting by splines directly taking into account the following considerations: -near optimal approximation by curves for a lot of vertices has high computational complexity [11,13]; less number of vertices is preferable; -noise and outliers on boundary caused by scanning process leads to nonsmooth outline; so, some filtration vertices of initial polygon is required; -polygon is a graphical path that consists of line segments only; on next stage we convert to curves only part of the segments. We solve min-# problem, that is we approximate N-vertex polygon P by another one Q: {q , .…”

Section: Contour Tracingmentioning

confidence: 99%

Generation of PDF with vector symbols from scanned document

et al. 2013

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The paper is devoted to the algorithm for generation of PDF with vector symbols from scanned documents. The complex multi-stage technique includes segmentation of the document to text/drawing areas and background, conversion of symbols to lines and Bezier curves, storing compressed background and foreground. In the paper we concentrate on symbol conversion that comprises segmentation of symbol bodies with resolution enhancement, contour tracing and approximation. Presented method outperforms competitive solutions and secures the best compression rate/quality ratio. Scaling of initial document to other sizes as well as several printing/scanning-to-PDF iterations expose advantages of proposed way for handling with document images. Numerical vectorization quality metric was elaborated. The outcomes of OCR software and user opinion survey confirm high quality of proposed method.

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“…There are a lot of studies in reconstruction of 2D images especially font and character images. Non-Roman character digitization such as Chinese [6,7] and Arabic [8,9] are the common application of 2D images curve fitting that are most researcher prefer to do on their research. According to [10], this type of character known as cursive, complex and needs more attentions.…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Shape Parameters of Beta-Spline Using Particle Swarm Optimization

Suliman

Afrouzi²

2018

IJET

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Beta-spline is an alternative curve for 2D font representation. It is preferred since it has G2 continuity and two shape parameters, that can be used to control the curve shape. These shape parameters can also be used to optimize the error between fitted curve and original data points. Commonly, most of the researcher use value of shape parameters of beta-spline as and or some of the researcher choose any random value of these two shape parameters that suitable to be used in beta-spline curve fitting. The values of shape parameters are very important since the values affect the total error of the fitted curves. Thus, in this paper, Particle Swarm Optimization (PSO) is employed to determine the optimum value of the two shape parameters that will optimize the approximation error of the fitted curve. The technique is applied on two fonts: ى and δ, and tested using various number of iterations and populations.

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An efficient technique for capturing 2D objects

Cited by 9 publications

References 35 publications

Optimal curve fitting approach to represent outlines of 2D shapes

Optimal curve fitting approach to represent outlines of 2D shapes

Generation of PDF with vector symbols from scanned document

Optimizing the Shape Parameters of Beta-Spline Using Particle Swarm Optimization

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