Region Extraction and Description through Planning.
MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER AND INFORMATION SCIENCE
Pagination or Media Count:
This paper examines several image segmentation algorithms which have been explored in the development of the VISIONS system. Each of these algorithms can be viewed as a variation on a basic theme the clustering of activity in feature space via histogram analysis, mapping these clusters back onto the image, and then isolating regions by analysis of the spatial relationships of the cluster labels. It is shown that the interaction between these two representations of data global feature information and spatial information provides a view that is lacking in either. The scene segmentation algorithms contain the following stages 1 PLAN reduce the amount of detail in the scene to a bare minimum by performing a fast simple segmentation into primary areas using spatial andor quantization compression. 2 REFINE resegment the scene with careful attention directed to the textural complexities of each region. The primitive transformations which are used include histogram clustering, region growing, data reduction by narrowing the quantization range, andor data reduction by spatially collapsing the data while extracting features. These algorithms have been implemented using a parallel, hierarchical computational structure. Comparisons of performance on several images are given. Author
- Computer Programming and Software
- Non-Radio Communications