Minfeng Chen

Guilin University of Electronic Technology

Papers

Total Citations

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About

Minfeng Chen is a researcher whose work lies at the intersection of robotics, computer vision, and color-based image processing. Chen’s most notable contribution is a foundational study on target recognition algorithms for robots, published in 2008, which has garnered 2 citations. This research, set against the backdrop of the Asian-Pacific robot contest, introduced an innovative eight-connection clustering algorithm based on color double thresholds in the HSI color space. By leveraging hue and saturation information, Chen’s method significantly improved the accuracy and efficiency of robot vision systems in identifying and tracking colored objects. This work has practical implications for autonomous robotics, particularly in dynamic environments where reliable visual recognition is critical. While Chen’s citation count is modest, the study represents a targeted advancement in real-time image processing for robotic applications. Chen’s research underscores a commitment to solving practical challenges in robotics, bridging theoretical algorithms with tangible, contest-driven implementations. For students and researchers exploring color-based vision systems, Chen’s work offers a clear, applied example of how clustering techniques can enhance robotic perception and autonomy.