Huamán-De la Vega, Susi

Profile Picture

Filters

20101
Reset filters

Settings

Citations

Publication Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    Publication
    Object segmentation in hyperspectral images using graph cuts based on active contours
    (2010) Huamán-De la Vega, Susi; Manian, Vidya; College of Engineering; Rodríguez, Néstor J.; Borges, José; Department of Electrical and Computer Engineering; Hajek, Darrell
    The interest in object segmentation on hyperspectral images is increasing and many approaches have been proposed to deal with this area. In this project, we develop an algorithm that combines both the active contours and the graph cut approaches for object segmentation in hyperspectral images. The active contours approach has the advantage of producing sub-regions with continuous boundaries. The graph cuts approach has emerged as a powerful optimization technique for minimizing energy functions while avoiding the problems of local minima inherent in other approaches. The combination of the two models has robust object segmentation capability because it has the ability to avoid the local minima and provide a more global result. Additionally, graph cuts guarantee continuity and produce smooth contours, free of self-crossing and uneven spacing problems. Our approach uses both spatial information and spectral information from hyperspectral images and it can segment more than one object in an image. We tested our algorithm using real and synthetic hyperspectral images, and obtained good results. This algorithm can be applied in many fields and it should represent an important advance in the field of object segmentation.