A satellite component contour extraction method for lightweight space mobile platforms

Abstract

Purpose

Owing to the complex space environment and limited computing resources, traditional and deep learning-based methods cannot complete the task of satellite component contour extraction effectively. To this end, this paper aims to propose a high-quality real-time contour extraction method based on lightweight space mobile platforms.

Design/methodology/approach

A contour extraction method that combines two edge clues is proposed. First, Canny algorithm is improved to extract preliminary contours without inner edges from the depth images. Subsequently, a new type of edge pixel feature is designed based on surface normal. Finally, surface normal edges are extracted to supplement the integrity of the preliminary contours for contour extraction.

Findings

Extensive experiments show that this method can achieve a performance comparable to that of deep learning-based methods and can achieve a 36.5 FPS running rate on mobile processors. In addition, it exhibits better robustness under complex scenes.

Practical implications

The proposed method is expected to promote the deployment process of satellite component contour extraction tasks on lightweight space mobile platforms.

Originality/value

A pixel feature for edge detection is designed and combined with the improved Canny algorithm to achieve satellite component contour extraction. This study provides a new research idea for contour extraction and instance segmentation research.

Citation

Li, Q., Zhu, Z. and Liang, J. (2023), "A satellite component contour extraction method for lightweight space mobile platforms", Aircraft Engineering and Aerospace Technology, Vol. 95 No. 8, pp. 1217-1226. https://doi.org/10.1108/AEAT-11-2022-0331