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@article{180167,
        author = {Aditya Digambar Kamble and MRS. SWATI D. GHULE},
        title = {Procedural Terrain Generation Using Perlin Noise},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {256-259},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180167},
        abstract = {Procedural 
terrain 
generation 
is 
a 
cornerstone technique in computer graphics and game 
development, enabling the automatic creation of 
expansive and detailed landscapes. This paper explores 
the use of Perlin noise — a gradient noise function —
 for generating realistic and high-quality terrains. By 
using Python and libraries like NumPy, Matplotlib, and 
the noise package, a scalable and customizable 3D 
terrain model is implemented and visualized. The 
generated terrain is enhanced using an intuitive color
mapping strategy that simulates natural features like 
water bodies, grasslands, mountains, and snow-capped 
peaks. The study examines the effectiveness of Perlin 
noise in maintaining visual coherence and randomness 
while preserving computational efficiency. The results 
demonstrate that Perlin noise based generation offers a 
versatile and controllable method for producing 
realistic virtual terrains with minimal manual 
intervention.},
        keywords = {},
        month = {May},
        }