Name
Abstract | ||
|---|---|---|
We describe a method for automatically detecting streaks in printed images using adaptive window-based image projections and mutual information. The proposed approach accepts a scanned image enclosing the defect and computes the projections across the entire image at different window sizes. The resulting traces collected from the projections are analyzed with a peak detection algorithm and subsequently correlated using normalized mutual information to pinpoint the location and width of streak(s). Finally, for a given peak, the window size is changed adaptively to identify and locate the intensity and length of the corresponding streak(s) while maximizing the signal-to-noise ratio. Results on synthetic and real-life images are provided to demonstrate the effectiveness of our proposed technique. (c) 2007 SPIE and IS&T. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1117/1.2816444 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
streak | Computer vision,Computer graphics (images),Computer science,Streak,Artificial intelligence | Journal |
Volume | Issue | ISSN |
16 | 4 | 1017-9909 |
Citations | PageRank | References |
2 | 0.53 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hector Santos Rosario | 1 | 2 | 0.53 |
| Eli Saber | 2 | 478 | 58.40 |
| Wencheng Wu | 3 | 3 | 0.93 |
| Kartheek Chandu | 4 | 16 | 2.77 |