999 resultados para Carta de color


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26 hojas : fotografías a color.

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47 hojas : ilustraciones, fotografías a color, muestras.

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[40] hojas : ilustraciones, fotografías.

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28 hojas : ilustraciones, fotografías.

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48 hojas : ilustraciones, fotografías.

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Los frutos sufren tras la recolección diversos cambios fisicoquímicos que determinan su calidad intrínseca. Uno de los cambios más importantes y manifiestos que ocurren durante la maduración, para muchos frutos es el del color. El resaltado mis común de las modificaciones de color es la pérdida de la pigmentación verde como consecuencia de la degradación de la clorofila, que va asociada a la síntesis o al desenmascaramiento de otros pigmentos. Los cambios de color o desaparición del color verde de la piel constituye un buen indicativo no destructivo del grado de madurez para muchos frutos, incluyendo el aguacate "Hass". Actualmente se viene realizando una extensa investigación direccionada a la detección no destructiva del grado de madurez de los frutos, desarrollando sistemas y experimentando sistemas y técnicas basadas en propiedades físicas de los productos. Sin embargo, para los frutos que presentan el cambio de color de piel durante la maduración, el análisis de estos cambios presenta diversas ventajas sobre otras técnicas, como la manipulación mínima de los frutos y la no necesidad de acoplamiento de sensores en la superficie del fruto. Además del potencial de utilización en procesos reales con alta productividad. Así varios investigadores han estudiado el color de los frutos con el fin de evaluar el grado de madurez de los mismos. Así Rood (1957), citado por Delwiche (1987), concluye que los mejores índices de madurez para el melocotón son por el orden de importancia la firmeza de la pulpa, color de la piel, color de la pulpa y contenido de clorofila de la pulpa. Sims et al. (1963) concluyen que la firmeza de la pulpa y el color de fondo pueden ser utilizados como índices de madurez para melocotones y sugiere la utilización del colorímetro "tristimulus" para el desarrollo de una carta colorimétrica para la evaluación de madurez. De la Plaza (1973), define los conceptos de" umbral de color de fondo" y de "umbral de firmeza" como licites superior e inferior, respectivamente, para la madurez de consumo de pera "Dr Jules Guyot". Delwiche et al. (1983,1985,1987) estudian las correlaciones entre la firmeza de la pulpa y otros índices de madurez y el color de fondo proponiendo una carta de colores y madurez. Martínez-Javega y Otero (1989) concluyen que hay una correlación entre la firmeza de la pulpa y el índice cromático obtenido a partir de las coordenadas Hunter L,a,b para el aguacate cv. "HASS" con distintos tratamientos de conservación. Estudios semejantes para otros productos se han referido: Bittner y Noris (1986); Long et al. (1973); Kramer (1976); Robbins y Moore (1990); Pai y Sastry(1990)L El presente trabajo tiene como objetivo estudiar los índices cromáticos obtenidos a partir de las coordenadas Hunter L, a, b para la piel y la pulpa de aguacate cv." HASS ".

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Mode of access: Internet.

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Purpose: To determine (a) the effect of different sunglass tint colorations on traffic signal detection and recognition for color normal and color deficient observers, and (b) the adequacy of coloration requirements in current sunglass standards. Methods: Twenty color-normals and 49 color-deficient males performed a tracking task while wearing sunglasses of different colorations (clear, gray, green, yellow-green, yellow-brown, red-brown). At random intervals, simulated traffic light signals were presented against a white background at 5° to the right or left and observers were instructed to identify signal color (red/yellow/green) by pressing a response button as quickly as possible; response times and response errors were recorded. Results: Signal color and sunglass tint had significant effects on response times and error rates (p < 0.05), with significant between-color group differences and interaction effects. Response times for color deficient people were considerably slower than color normals for both red and yellow signals for all sunglass tints, but for green signals they were only noticeably slower with the green and yellow-green lenses. For most of the color deficient groups, there were recognition errors for yellow signals combined with the yellow-green and green tints. In addition, deuteranopes had problems for red signals combined with red-brown and yellow-brown tints, and protanopes had problems for green signals combined with the green tint and for red signals combined with the red-brown tint. Conclusions: Many sunglass tints currently permitted for drivers and riders cause a measurable decrement in the ability of color deficient observers to detect and recognize traffic signals. In general, combinations of signals and sunglasses of similar colors are of particular concern. This is prima facie evidence of a risk in the use of these tints for driving and cautions against the relaxation of coloration limits in sunglasses beyond those represented in the study.

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We investigated influences of optics and surround area on color appearance of defocused, small narrow band photopic lights (1’ arc diameter, λmax 510 - 628 nm) centered within a black annulus and surrounded by a white field. Participants included seven normal trichromats with L- or M-cone biased ratios. We controlled chromatic aberration with elements of a Powell achromatizing lens and corrected higher-order aberrations with an adaptive-optics system. Longitudinal chromatic aberrations, but not monochromatic aberrations, are involved in changing appearance of small lights with defocus. Surround field structure is important because color changes were not observed when lights were presented on a uniform white surround.

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A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.