A segmentation method for images compressed by fuzzy transforms
Fuzzy Sets and Systems
| Hi-index | 0.00 |
This paper presents a fast image segmentation algorithmfor extracting areas-of-interest ("hotspots")from video sequences. Because video hotspots, which are the visual analogues of HTML hyperlinks, highly depend on a user's interest, it is very difficult to automatically extract the exactoutlines of objects of interest in videos. Our approach ofinteractive video hotspot retrieval is to provide candidatehotspots with segmented re ions of video frames when requested, and web designers using the tool for web site creation may select the area (or areas)he is interested in as a video hotspot. This segmentation algorithm follows a three step coarse-to-fine scheme. The original image is first divided into blocks and a block-merging process is appliedto get a coarse segmentation. Then we represent the presegmented image as a graph where the value of edges in this graph are evaluated based on multi-features, and by using a minimum spanning tree searching algorithm, we mergethe vertices in the graph to generate the segmented regionsof the image. Finally, we refine the boundary of segmentedregions on the pixel level using an improved K-means clustering algorithm. This segmentation algorithm is fast and efficient and our signal segmentation results compare favorably with the results obtained using manual outlining. We also provide a convenient way for the web page designer to select multiple regions as a video hotspot. Our method allows the designer to click on an image during video playback and to get a segmented image almost instantly. The extracted video hotspots can then be used for video hyperlinks, an extension of the general concept of hyperlink to interactive videos.