In recent gears, the theory of Rough Sets hos gained pnromount importance and npplicabilitg in diverse onaa of nseareh, especidly in Dota Mining, Knowledge Discovery, ArtijXal htelligence and Information Sgstems nnolysis. Rough Se& have ob0 been w e d in imoging, however, the opplicotion of Rough Sets for color image nnnly-ais hoa yet to be jUly investigoted. In this pnper, on interesting strategy for color imoge segmentotion wing Rough Set Theory has been pn-
Rented.A new concept of encnutotion of the histogram, cnlled histon, hm been pmponed for the vinunlization of multi-dimsnmonal anlor informotion in an integrated foshwn, and its npplicabiwg town& boundnty peginn analynin has been nhoum. The hhton rxmwlntes with the upper approzimotion of n ret such that 011 element8 belonging to this set are clossified ns possibly belonging to the same segment, or segments showing nimilar color value. The pmpoaed encnmtation pmviden a dimct meow of segregnting pool of inhomogenow regions into its components. Ezperimental results for various images hove been presented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.