In this paper, we propose a novel autonomous Martian rock detection framework via superpixel segmentation. Different from current state-of-the-art pixel-level rock segmenting methods, the proposed method deals with this issue in region level. Image is splitted into homogeneous regions based on intensity information and spatial layout. The heart of proposed framework is to enhance such region contrast. Then, rocks can be simply segmented from the resulting contrast-map by an adaptive threshold. Our method is efficient in dealing with large image and only few parameters need to set. Preliminary experimental results show that our algorithm outperforms edge-based methods in various grayscale rover images.
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This work was supported by National Natural Science Foundation of China (NSFC) (Grant Nos. 61503102, 61701225).
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Li, G., Geng, Y. & Xiao, X. Multi-scale rock detection on Mars. Sci. China Inf. Sci. 61, 102301 (2018). https://doi.org/10.1007/s11432-017-9277-x
- Mars rover
- rock detection
- superpixel segmentation
- region contrast
- image enhancement