Title :
Contextual image filtering
Author_Institution :
Div. of Math. & Inf. Sci., CSIRO, Sydney, NSW, Australia
Abstract :
A morphological attribute filter uses a criterion to decide which connected components to preserve and which to remove. So far, these criteria considered only attributes of each component individually. In this paper, a new type of attribute filter is proposed, where context attributes of a component are considered. These context attributes describe how that component relates to other components in the image. Alignment, distance, and similarities in size, shape, and orientation between the individual components can be used to determine which components belong to the same context. The resulting contextual filter can be used to preserve only those components which visually appear to belong to a certain group of similar components. It can be used to detect textures or patterns of connected components. Although similar results could be obtained by applying a dedicated series of conventional filters, the proposed algorithm requires at most a redefinition of some rules instead of the elaborate design and implementation of a complete new method.
Keywords :
image enhancement; attribute filter; context attributes; contextual image filtering; patterns detection; texture detection; Algorithm design and analysis; Australia; Computer vision; Image analysis; Information filtering; Information filters; Level set; Morphology; Object detection; Shape measurement;
Conference_Titel :
Image and Vision Computing New Zealand, 2009. IVCNZ '09. 24th International Conference
Conference_Location :
Wellington
Print_ISBN :
978-1-4244-4697-1
Electronic_ISBN :
2151-2205
DOI :
10.1109/IVCNZ.2009.5378393