Supervised grayscale thresholding based on transition regions
Image and Vision Computing
Scale selection for supervised image segmentation
Image and Vision Computing
| Hi-index | 14.98 |
Image segmentation can be treated as a pixel classification problem. This classification may be done by measuring a set of features at each point and defining a decision surface in the feature space. This method is commonly used in multispectral images, but there is no obvious choice for the feature set in the case of monochromatic images. Ihis paper makes use of a two-dimensional feature set consisting of gray level and edge value. Ihe structure of this feature space is analyzed, and several plausible decision surfaces are suggested. These are compared experimentally on a set of FLIR test images.