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An optimal B-spline approach for vectorizing raster image outlines.

Samreen Abbas¹, Malik Zawwar Hussain², Qurat Ul-Ain³

¹Department of Mathematics, GC Women University, Sialkot, Pakistan.

|August 26, 2024

Summary

This summary is machine-generated.

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This study introduces an automatic algorithm for digital image outline vectorization using trigonometric B-spline and Genetic Algorithm (GA) optimization. The method effectively captures planar object outlines for improved image processing.

Area of Science:

Computer Vision
Image Processing
Computational Geometry

Background:

Accurate outline extraction is vital for digital image vectorization.
Existing methods may lack efficiency or robustness in capturing complex object boundaries.

Purpose of the Study:

To present an effective and automatic algorithm for outline vectorization of planar objects in digital images.
To utilize trigonometric B-spline for precise curve fitting and Genetic Algorithm (GA) for parameter optimization.

Main Methods:

Boundary detection and corner recognition to identify key features.
Break point identification for segmenting object outlines.
Curve fitting using a proposed trigonometric B-spline, optimized by Genetic Algorithm (GA).

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Main Results:

The algorithm successfully vectorized outlines of planar objects in raster (bitmap) images.
Validation demonstrated the robustness and effectiveness of the proposed scheme.

Conclusions:

The developed algorithm provides an efficient and automatic solution for digital image outline vectorization.
The integration of trigonometric B-spline and GA offers a robust approach for capturing object boundaries.