I document my ISRO Craters and Boulders Detection project as an academic, research-practice, and GitHub-portfolio project focused on lunar terrain analysis and space-mission-related applications. The README describes its aims and structure, but does not identify a particular mission deployment or specify a detection algorithm.
My ISRO-Craters-and-Boulders-Detection-Project repository is on @Mousam098's GitHub.
My repository has 1 star.
My repository was started 2026-07, last updated 2026-07.
My project detects and analyzes craters and boulders from planetary surface images.
Craters and boulders provide useful information about surface age, terrain roughness, impact history, geological structure, and landing safety.
Manual identification of craters and boulders from high-resolution planetary images is time-consuming.
- My README lists these mission-related applications: Safe landing-site selection; Rover navigation; Terrain hazard detection; Geological study; Surface age estimation; Mission planning.
- My README lists image upload and analysis, visual display of processed detections, detected-object counts, and image preprocessing as project features.
My project uses Python; OpenCV; NumPy; Matplotlib; Streamlit; Pillow; Image Processing; Computer Vision.
My declared repository structure includes app/app.py; src/crater_detection.py; src/boulder_detection.py; src/image_processing.py; src/utils.py; dataset/craters/; dataset/boulders/; dataset/test_images/; outputs/detected_craters/; outputs/detected_boulders/; outputs/results/; assets/sample_images/; requirements.txt; README.md; .gitignore.
The README presents the project as suitable for an ISRO-themed academic demonstration and as easy to understand, run, and extend. It frames image processing and computer vision as ways to automate or simplify manual identification; it does not document implementation details, detection performance, dataset sizes, or benchmark results.
I note that planetary surface analysis is an important part of space exploration.
I can use the system to study lunar terrain images and support automated terrain understanding for space mission-related analysis.
I focus on identifying surface features useful in planetary exploration, lunar mapping, landing-site analysis, and terrain understanding.