1Mr. Kunchala Ramesh, 2Pamidi Sowmya,3Ranga Sonia,4P. Prasanna 03 08 Terrain analysis has become an important application of computer vision in various fields such as autonomous navigation robotics agriculture and environmental monitoring Accurate identification of different terrain types helps intelligent systems make better decisions in realworld environments This project presents the development of a Computer Visionbased Terrain Analysis System using Deep Learning techniques The proposed system utilizes a Convolutional Neural Network CNN to classify terrain images into four categories Grass Terrain Marshy Terrain Rocky Terrain and Sandy Terrain Image preprocessing techniques such as resizing and normalization are applied to improve classification performance The CNN model is developed using TensorFlow and Keras while OpenCV is used for image processing A Flaskbased web application provides a simple interface for uploading terrain images and displaying prediction results The proposed system improves classification accuracy by automatically extracting important visual features without manual intervention It provides an efficient reliable and userfriendly solution for automated terrain recognition and can be applied in autonomous vehicles precision agriculture robotic navigation and environmental monitoring Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026