TY - GEN
T1 - Improved HSI color space for color image segmentation
AU - Alvarado-Cervantes, Rodolfo
AU - Felipe-Riveron, Edgardo M.
PY - 2012
Y1 - 2012
N2 - We present an interactive, semiautomatic image segmentation method that processes the color information of each pixel as a unit, thus avoiding color information scattering. The color information of every pixel is integrated in the segmented image by an adaptive color similarity function designed for direct color comparisons. The border between the achromatic and chromatic zones in the HSI color model has been transformed in order to improve the quality of the pixels segmentation when their colors are very obscure and very clear. The color integrating technique is direct, simple and computationally inexpensive, and it has also good performance in low chromaticity and low contrast images. It is shown that segmentation accuracy is above 95% as average and that the method is fast. These results are significant when compared to other solutions found in the current literature.
AB - We present an interactive, semiautomatic image segmentation method that processes the color information of each pixel as a unit, thus avoiding color information scattering. The color information of every pixel is integrated in the segmented image by an adaptive color similarity function designed for direct color comparisons. The border between the achromatic and chromatic zones in the HSI color model has been transformed in order to improve the quality of the pixels segmentation when their colors are very obscure and very clear. The color integrating technique is direct, simple and computationally inexpensive, and it has also good performance in low chromaticity and low contrast images. It is shown that segmentation accuracy is above 95% as average and that the method is fast. These results are significant when compared to other solutions found in the current literature.
KW - Achromatic zone definition
KW - Adaptive color similarity function
KW - Color image segmentation
KW - Improved HSI color model
UR - http://www.scopus.com/inward/record.url?scp=84865598640&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33275-3_43
DO - 10.1007/978-3-642-33275-3_43
M3 - Contribución a la conferencia
SN - 9783642332746
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 348
EP - 354
BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings
T2 - 17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012
Y2 - 3 September 2012 through 6 September 2012
ER -