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Least-squares color Halftoning Algorithm Based on Clustering Analysis
| Content Provider | Semantic Scholar |
|---|---|
| Author | He, Zifen Zhang, Yinhui |
| Copyright Year | 2015 |
| Abstract | We presents a new method for color printers. Our algorithm applies to both a color printer model and a model for the human visual system (HVS). The method strives to minimize the perceived error between the continuous original image and the halftone image. The color printer models can account for a variety of printer characteristics. We propose a specific printer model that accounts for overlap between neighboring dots of ink and spectral absorption properties of the inks. The color image is partitioned into several regions using clustering segmentation method, whose performance depends on the selection of distance metrics. Each clustering uses the least-squares model-based(Lsmb) algorithm to obtain halftone image. A performance measure for halftone images is used to evaluate our algorithm. Analysis and simulation results show that the proposed algorithm produces better color halftone image quality when we increase the number of clustering with a certain range. |
| File Format | PDF HTM / HTML |
| DOI | 10.2991/isrme-15.2015.282 |
| Alternate Webpage(s) | https://download.atlantis-press.com/article/18470.pdf |
| Alternate Webpage(s) | https://doi.org/10.2991/isrme-15.2015.282 |
| Journal | ICIS 2015 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
