YOLOv26-based automated crater detection and geometric measurement using Chandrayaan-2 Orbiter High Resolution Camera (OHRC) imagery

Meenakshi Sarkar
Space Application Centre, Indian Space Research Organization, Ahmedabad 380015, India
Prit Gajjar
Space Application Centre, Indian Space Research Organization, Ahmedabad 380015, India

Article ID: 4398

Keywords: lunar crater detection, Chandrayaan-2, YOLO (You Only Look Once), SAM (Segment Anything Model), OHRC (Orbiter High Resolution Camera) imagery, lunar surface analysis, crater geometry estimation

Abstract

Accurate detection and measurement of lunar craters are crucial for a better understanding of the geological history and evolution of the Moon’s surface. Manually detecting and measuring craters using high-resolution images is not only tedious but may also involve a certain amount of subjectivity. What makes this proposal innovative is the combination of the You Only Look Once (YOLO) algorithm with the Segment Anything Model for accurate segmentation of craters’ pixels and measurement of their geometrical properties. In this framework, the locations of the craters are automatically detected using the YOLOv26 algorithm, followed by accurate determination of the crater regions using the Segment Anything Model (SAM). Finally, the accurate determination of the diameter, radius, and surface area of the craters is carried out using the pixel measurement and scale factor conversion technique. This approach will be trained and tested using a dataset comprised of about 12,000 images obtained by dividing the Orbiter High Resolution Camera (OHRC) lunar imagery into image patches of 640 × 640 dimensions and divided in the ratio of training set: validation set: test set as 70:20:10. This model gave a precision value of 91.5%, a recall of 88.6%, mAP@50 of 95.6%, and mAP@50–95 of 88.6%, thereby outperforming all other versions of YOLO that were analysed and showing strong competency.

Published

2026-05-11

How to Cite

Sarkar, M., & Gajjar, P. (2026). YOLOv26-based automated crater detection and geometric measurement using Chandrayaan-2 Orbiter High Resolution Camera (OHRC) imagery. Computing and Artificial Intelligence, 4(2). https://doi.org/10.59400/cai4398

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Vol. 4 No. 2 (2026)

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Article

This work is licensed under a Creative Commons Attribution 4.0 International License.

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