Granulometries are powerful and versatile tools in image analysis and pattern spectra, or size distribulions, are a simple method of extracting information from an image using these granulometries. One of the drawbacks of the traditional pattern spectra, the lack of spatial information about connected components within images, is addressed in this project by introducing three extensions to the regular area pattern spectra: one based on moments, one based on translation of the components within the image, and one based on multi-scale connectivity. These three extensions are tested in the field of content-based image retrieval: are they able to retrieved images from an image-database, that are similar in some way to a certain, user-provided, query-image? This is a question that is interesting for fields like intelligent multimedia and web searches (search engines).
