Method for extracting sea and air target candidate boxes under SVDD-TSVM

Guanhua Wang; Zhongmin Zhang; Zihang Lin; Kexin Zhang

doi:10.1117/12.3031606

18 July 2024 Method for extracting sea and air target candidate boxes under SVDD-TSVM

Guanhua Wang, Zhongmin Zhang, Zihang Lin, Kexin Zhang

Proceedings Volume 13179, International Conference on Optics and Machine Vision (ICOMV 2024); 131790V (2024) https://doi.org/10.1117/12.3031606
Event: International Conference on Optics and Machine Vision (ICOMV 2024), 2024, Nanchang, China

Abstract

In order to fully perceive the environment in maritime navigation activities, multi-target detection tasks are required. The commonly used method for extracting candidate boxes in the pre task of object detection in high-resolution sea and air images is inefficient and computationally intensive. This article combines color name nonlinear color mapping and grayscale co-occurrence matrix information to design manual features. By building an SVDD-TSVM joint classifier to reduce the missed detection rate of foreground targets, a grid based candidate box extraction method is constructed. A selfmade dataset and comparison method are used for simulation verification. The results show that the missed detection rate of the SVDD-TSVM joint classifier designed in this article is somewhat reduced compared to other comparison methods, And the candidate box extraction method in this article reduced the number of invalid candidate boxes by an average of 87%, and the detection time by an average of 69.5%. The self-made dataset NAME-D and some code in this article have been uploaded to https://github.com/guanhar/tolabin/.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Guanhua Wang, Zhongmin Zhang, Zihang Lin, and Kexin Zhang "Method for extracting sea and air target candidate boxes under SVDD-TSVM", Proc. SPIE 13179, International Conference on Optics and Machine Vision (ICOMV 2024), 131790V (18 July 2024); https://doi.org/10.1117/12.3031606

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KEYWORDS

Object detection

Image classification

Feature extraction

Target detection

Detection and tracking algorithms

Visualization

Support vector machines

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