Abstract
Color-vision-based applications for mobile phones has become a subject of special interest lately. It would be interesting to investigate an unsupervised, adaptive, and fast algorithm that can classify color components into color clusters. We propose a hierarchical clustering approach using a single-linkage algorithm and a k-means clustering approach to color classification for color-based image code recognition in mobile computing environments. We also measured the performance of the proposed algorithms by color channel stretch, which is a simple color-correction method. Experimental results show that the single-linkage method is more robust than previous algorithms used in experiments with varying cameras and print materials. In particular the k-means-based method with color channel stretching has the highest performance and is the most robust under varying environment conditions such as illuminants, cameras, and print materials.
Original language | English |
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Pages (from-to) | 2326-2345 |
Number of pages | 20 |
Journal | Applied Optics |
Volume | 47 |
Issue number | 13 |
DOIs | |
Publication status | Published - 2008 May 1 |
All Science Journal Classification (ASJC) codes
- Atomic and Molecular Physics, and Optics
- Engineering (miscellaneous)
- Electrical and Electronic Engineering