| Paper: | IMDSP-P2.11 | ||
| Session: | Restoration | ||
| Time: | Tuesday, May 18, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Image and Multidimensional Signal Processing: Image and Video Filtering | ||
| Title: | AN EFFICIENT BINARY IMAGE ACTIVITY DETECTOR BASED ON CONNECTED COMPONENTS | ||
| Authors: | Patrice Simard; Microsoft Research | ||
| Henrique Malvar; Microsoft Research | |||
| Abstract: | Activity detection on binary images can be a useful part of image processing for detecting noise, texture, printed text, or dithering. In this paper we present an image activity detector based on computing a density of selected connected components. Connectedness is a useful property because it is present in individual printed letters, lines, and edges. In contrast, salt-and-pepper noise and dithering are typically composed of a large number of disconnected patterns. By filtering the connected components based on size, we can measure different kind of activities and segment or filter the image accordingly. The activity detector is extremely efficient and can typically be run in a fraction of the time it takes to compute a run-length encoding version of the image. As an example, we built a noise removal filter based on the density of connected component which is both faster and better than a conventional median filter. | ||
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