As part of my M.Tech thesis at IIT Bhilai, I am working on automated crater detection on lunar and planetary surfaces using a combination of computer vision, image processing, and deep learning techniques. My research focuses on designing robust algorithms that can accurately identify craters of various sizes under challenging conditions such as shadowing, uneven illumination, and surface noise. I utilize convolutional neural networks (CNNs), transformer-based architectures, and attention mechanisms to enhance detection accuracy. The models are trained on high-resolution lunar imagery from ISRO’s Chandrayaan missions, complemented by other publicly available datasets. This work plays a critical role in supporting future lunar exploration by aiding in surface analysis, hazard detection, and landing site selection.

Core Technologies

• Deep Learning (CNNs, Transformers)
• Image Preprocessing (Histogram Equalization, Filtering)
• OpenCV, TensorFlow, PyTorch
• MATLAB for optimization and control systems
• Remote sensing datasets (LRO, HiRISE)
• ISRO's Chandrayaan Data(TMC&DTM)