Kexian Xiao
Papers
1
Total Citations
4
H-Index
1
About
Kexian Xiao is a researcher whose work bridges computer vision and cultural heritage preservation, with a particular focus on automated image analysis for traditional Chinese games. His most cited paper, “Illumination invariant Chinese chessboard reconstruction based on color image” (2009, 4 citations), introduces a novel method that combines binarized Gabor filters and the Hough transform to reconstruct Chinese chessboards directly from color images. By applying Gabor transforms to retain only lines of interest, Xiao’s approach achieves robustness against varying illumination conditions—a critical challenge in real-world image processing. This contribution demonstrates his expertise in feature extraction and pattern recognition, offering practical solutions for digitizing and analyzing traditional artifacts. While his citation count remains modest, Xiao’s work highlights the intersection of computational techniques with cultural applications, providing a foundation for further research in invariant image reconstruction and heritage digitization. His focus on illumination invariance and line detection underscores a commitment to developing reliable algorithms for complex visual environments, making his research relevant for students and scholars interested in applied computer vision and cultural informatics.
Research Focus
Key Achievements
Top Papers
- 1