Deepsikha Bhattacharjee

National Institute of Technology Agartala

Papers

Total Citations

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About

Deepsikha Bhattacharjee is a researcher at the intersection of computer vision, digital art, and automated manufacturing. Her primary research focuses on image processing techniques for robotic and CNC (Computer Numerical Control) applications, particularly in the domain of vectorization and fractal deployment. In her notable 2021 work, "Generating Vectors from Images using Multi-Stage Edge Detection for Robotic Artwork," she addressed a critical challenge in converting edge-detected artworks into vector formats suitable for CNC devices, proposing a multi-stage edge detection pipeline that enhances the fidelity of robotic artwork reproduction. This work has garnered 2 citations, establishing a foundation for her subsequent research. Expanding her scope, Bhattacharjee's 2023 paper, "Deployment of Fractals through CNC Devices," explores the propagation of iconic fractal patterns—including the Sierpinski gasket, Barnsley fern, fractal tree, and Koch snowflake curve—via CNC machinery. With 2 citations, this work bridges mathematical beauty and practical fabrication, demonstrating how complex, self-similar geometries can be precisely realized in physical media. Her contributions are particularly valuable for artists, engineers, and researchers seeking to automate the creation of intricate, algorithmically generated designs, positioning her as a key figure in the emerging field of computational artistry and digital fabrication.