article · 2023

Algorithm for minimum bounding rectangle based on key point set

Cited by 0Abstract and details only

Abstract

This paper proposes a ship detection method based on contour extraction networks and minimum bounding box generation algorithms. The proposed method utilizes contour extraction networks to extract the contour of the ship target and generate a set of key points. Then, the minimum bounding box generation algorithm is used to transform these key points into the rotational detection box of the target, which can more accurately describe the shape and orientation of ships, thus improving the accuracy and reliability of detection. The experimental results show that the proposed method can effectively detect ships of various orientations and postures and has better performance than traditional rectangular box detection methods. The paper compares rotated bounding box detection methods based on traditional machine learning and deep learning and concludes that rotated bounding box detection methods based on deep learning can better solve the problem of ship detection in complex situations, but require a large amount of data for training and may require a higher computational cost. Finally, the paper introduces the Minimum Bounding Rectangle Algorithm used in the instance segmentation process.

Cite this paper

APA 7

liang, F., Wang, L., & Yu, J. (2023). Algorithm for minimum bounding rectangle based on key point set. https://doi.org/10.1117/12.2684686

MLA 9

liang, fengqi, et al. “Algorithm for minimum bounding rectangle based on key point set.” 2023, p. 38, https://doi.org/10.1117/12.2684686.

Chicago

liang, fengqi, Licai Wang, and Jintao Yu. 2023. “Algorithm for minimum bounding rectangle based on key point set.” https://doi.org/10.1117/12.2684686.

Harvard

liang, F., Wang, L. and Yu, J. (2023) ‘Algorithm for minimum bounding rectangle based on key point set’. Available at: https://doi.org/10.1117/12.2684686.

BibTeX

@article{liang2023algorithm,
  title = {{Algorithm for minimum bounding rectangle based on key point set}},
  author = {liang, fengqi and Wang, Licai and Yu, Jintao},
  pages = {38},
  year = {2023},
  doi = {10.1117/12.2684686}
}

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