Estimating the Illuminant Color from the Shading of a Smooth Surface

\0\05{\0\0\0\0\0\0\0\0 a uniform wall illuminated by a spot light often gives a strong impression of the illuminant color. How can it be possible to know if it is a white wall illuminated by yellow light or a yellow wall illuminated by white light? If the wall is a Lambertian reflector, it would not be possible to tell the difference. However, in the real world, some amount of specular reflection is almost always present. In this memo, it is shown that the computation is possible in most practical cases.

Study of adsorption of methylene blue and new methylene blue in liquid-solid interface by slab optical waveguide spectroscopy

A slab optical waveguide (SOWG) has been used for study of adsorption of both methylene blue (MB) and new methylene blue (NMB) in liquid-solid interface. Adsorption characteristics of MB and NMB on both bare SOWG and silanized SOWG by octadecyltrichlorosilane (ODS) were compared. Effect of pH on adsorption on MB and NMB was investigated. Binding rate constant analysis showed that both MB and NMB on bare SOWG demonstrates larger association constants than those on ODS-SOWG. Interactions of NIB and NMB on bare SOWG and ODS-SOWG were analyzed by molecular mechanics calculation method. The binding energy change was in the following order: ENMB-bare > EMB-bare > ENMB-ODS > EMB-ODS. (c) 2004 Elsevier B.V. All rights reserved.

Using hybrid knowledge engineering and image processing in color virtual restoration of ancient murals

IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 5, pp. 1338-1343, 2003.

Pink Worlds and Blue Worlds: A Portrait of Intimate Polarity

Griffiths, Merris, 'Pink Worlds and Blue Worlds: A Portrait of Intimate Polarity', In: 'Small Screens: television for children', D. Buckingham (Ed.), (London: Leicester University Press), pp. 159-184, 2002 RAE2008

Carta de color.

26 hojas : fotografías a color.

Carta de color y manual de tintorería para la palma estera.

47 hojas : ilustraciones, fotografías a color, muestras.

Diversificación del color : mejoramiento de la materia prima.

13 hojas.

Productos funcionales y artísticos elaborados con enchapados en tamo al natural y a color mostrando materiales y fases del proceso.

19 hojas : ilustraciones, fotografías a color

Monturas de cuero recubiertas con pellones y gualdrapas tejidas con hilos de color, de los indígenas Wayúu Guajira.

11 hojas : ilustraciones, fotografías a color.

Muestras de productos funcionales y decorativos elaboraos en cerámica esmaltada a color.

27 hojas : ilustraciones, fotografías

Skin Color-Based Video Segmentation under Time-Varying Illumination

A novel approach for real-time skin segmentation in video sequences is described. The approach enables reliable skin segmentation despite wide variation in illumination during tracking. An explicit second order Markov model is used to predict evolution of the skin-color (HSV) histogram over time. Histograms are dynamically updated based on feedback from the current segmentation and predictions of the Markov model. The evolution of the skin-color distribution at each frame is parameterized by translation, scaling and rotation in color space. Consequent changes in geometric parameterization of the distribution are propagated by warping and resampling the histogram. The parameters of the discrete-time dynamic Markov model are estimated using Maximum Likelihood Estimation, and also evolve over time. The accuracy of the new dynamic skin color segmentation algorithm is compared to that obtained via a static color model. Segmentation accuracy is evaluated using labeled ground-truth video sequences taken from staged experiments and popular movies. An overall increase in segmentation accuracy of up to 24% is observed in 17 out of 21 test sequences. In all but one case the skin-color classification rates for our system were higher, with background classification rates comparable to those of the static segmentation.

Color Region Grouping and Shape Recognition with Deformable Models

A new deformable shape-based method for color region segmentation is described. The method includes two stages: over-segmentation using a traditional color region segmentation algorithm, followed by deformable model-based region merging via grouping and hypothesis selection. During the second stage, region merging and object identification are executed simultaneously. A statistical shape model is used to estimate the likelihood of region groupings and model hypotheses. The prior distribution on deformation parameters is precomputed using principal component analysis over a training set of region groupings. Once trained, the system autonomously segments deformed shapes from the background, while not merging them with similarly colored adjacent objects. Furthermore, the recovered parametric shape model can be used directly in object recognition and comparison. Experiments in segmentation and image retrieval are reported.