"Fabi\u00E1n, Tom\u00E1\u0161" . "RIV/61989100:27240/10:86077663!RIV12-MPO-27240___" . . "mean-shift algorithm; image segmentation; geodesic distance; euclidean distance"@en . "Advances in visual computing : 6th international symposium, ISVC 2010 : : proceedings, parts I-III" . "5"^^ . "000290358400032" . "978-3-642-17276-2" . . . . . "10.1007/978-3-642-17277-9_32" . "A new mean-shift technique, blurring mean-shift with a restricted dataset modification, is presented. It is mainly intended for applications in image processing since, in this case, the coordinates of the points entering into the mean-shift procedure may be obviously split into two parts that are treated in different ways: The spatial part (geometrical position in image) and the range part (colour/brightness). The basic principle is similar as in the blurring mean-shift algorithm. In contrast to it, the changes of the dataset are restricted only to the range values (colour/brightness); the spatial parts do not change. The points that are processed during computation may be viewed as points of a certain image that evolves during the iterations. We show that the process converges. As a result, an image is obtained with the areas of constant colour/brightness, which can be exploited for image filtering and segmentation. The results of testing are presented showing that the algorithm is useful." . "Springer-Verlag" . "Las Vegas" . . "[145D0A5CF385]" . "P(FR-TI1/262)" . "A new mean-shift technique, blurring mean-shift with a restricted dataset modification, is presented. It is mainly intended for applications in image processing since, in this case, the coordinates of the points entering into the mean-shift procedure may be obviously split into two parts that are treated in different ways: The spatial part (geometrical position in image) and the range part (colour/brightness). The basic principle is similar as in the blurring mean-shift algorithm. In contrast to it, the changes of the dataset are restricted only to the range values (colour/brightness); the spatial parts do not change. The points that are processed during computation may be viewed as points of a certain image that evolves during the iterations. We show that the process converges. As a result, an image is obtained with the areas of constant colour/brightness, which can be exploited for image filtering and segmentation. The results of testing are presented showing that the algorithm is useful."@en . . "0302-9743" . "2010-11-29+01:00"^^ . "Blurring mean-shift with a restricted data-set modification for applications in image processing" . . . "Berl\u00EDn" . "Blurring mean-shift with a restricted data-set modification for applications in image processing"@en . . "27240" . . . . . "Blurring mean-shift with a restricted data-set modification for applications in image processing" . "Krumnikl, Michal" . "Gaura, Jan" . . "Blurring mean-shift with a restricted data-set modification for applications in image processing"@en . "Sojka, Eduard" . . . "RIV/61989100:27240/10:86077663" . "\u0160ruba\u0159, \u0160t\u011Bp\u00E1n" . . "249072" . "5"^^ . . . "10"^^ . .