TY - GEN
T1 - Automatic palette identification of colored graphics
AU - Lacroix, Vinciane
PY - 2010
Y1 - 2010
N2 - The median-shift, a new clustering algorithm, is proposed to automatically identify the palette of colored graphics, a pre-requisite for graphics vectorization. The median-shift is an iterative process which shifts each data point to the "median" point of its neighborhood defined thanks to a distance measure and a maximum radius, the only parameter of the method. The process is viewed as a graph transformation which converges to a set of clusters made of one or several connected vertices. As the palette identification depends on color perception, the clustering is performed in the L*a*b* feature space. As pixels located on edges are made of mixed colors not expected to be part of the palette, they are removed from the initial data set by an automatic pre-processing. Results are shown on scanned maps and on the Macbeth color chart and compared to well established methods.
AB - The median-shift, a new clustering algorithm, is proposed to automatically identify the palette of colored graphics, a pre-requisite for graphics vectorization. The median-shift is an iterative process which shifts each data point to the "median" point of its neighborhood defined thanks to a distance measure and a maximum radius, the only parameter of the method. The process is viewed as a graph transformation which converges to a set of clusters made of one or several connected vertices. As the palette identification depends on color perception, the clustering is performed in the L*a*b* feature space. As pixels located on edges are made of mixed colors not expected to be part of the palette, they are removed from the initial data set by an automatic pre-processing. Results are shown on scanned maps and on the Macbeth color chart and compared to well established methods.
KW - clustering
KW - mean-shift
KW - palette extraction
UR - http://www.scopus.com/inward/record.url?scp=77954607033&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-13728-0_6
DO - 10.1007/978-3-642-13728-0_6
M3 - Conference contribution
AN - SCOPUS:77954607033
SN - 364213727X
SN - 9783642137273
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 61
EP - 68
BT - Graphics Recognition
T2 - 8th IAPR Workshop on Graphics Recognition, GREC 2009
Y2 - 22 July 2009 through 23 July 2009
ER -