Archisman Bhaumik
Papers
1
Total Citations
2
H-Index
1
About
Archisman Bhaumik is a researcher whose work sits at the intersection of computer vision, image processing, and robotics, with a particular focus on enabling machines to interpret and recreate visual art. His key research area involves developing algorithms for the vectorisation of images, a critical step for feeding data to computer numerical controlled (CNC) vector devices used in robotic artwork. Bhaumik’s major contribution, detailed in his most-cited paper “Generating Vectors from Images using Multi-Stage Edge Detection for Robotic Artwork” (2021, 2 citations), addresses the challenge of converting edge-detected artworks into precise vector paths. By proposing a multi-stage edge detection framework, he improves the fidelity of vectorisation, allowing robotic systems to produce more accurate and aesthetically pleasing outputs. While his citation count is modest, this work represents a foundational step in bridging digital image processing and physical robotic creation. Bhaumik’s research is notable for its practical application in automated art generation, offering a pipeline that could streamline workflows in digital fabrication and creative robotics. His efforts highlight the growing synergy between computational techniques and artistic expression, making his work relevant for students and researchers exploring the boundaries of machine vision and robotic craftsmanship.
Research Focus
Key Achievements
Top Papers
- 1