Abstract: We present a rough and an accurate segmentation of natural color images using a fuzzy region-growing algorithm. In the proposed method, the color difference and the color gradient are used as the pixel features to produce an accurate segmentation, while the local fractal dimension is used as the region feature to yield a rough segmentation in a natural color image. The effectiveness of the proposed method is confirmed through computer simulations that demonstrate a rough segmentation at the fine-texture regions and an accurate segmentation at the strong-edge regions simultaneously.

Abstract: We describe a low-impact method for coloring interfaces harmoniously. The method uses a model that characterizes the overall image including the need for distinguishability between interface components. The degree of visual distinction between one component and other components, and its color strength (which increases with its importance and decreases with its size and longevity), are used in generating a rigid ball-and-stick 'color molecule,' which represents the color relationships between the interface components. The shape of the color molecule is chosen to conform to standard principles of color harmony (like colors harmonize, complementary colors harmonize, cycles in the color space harmonize, and so on). The color molecule's shape is fixed, but its position and orientation within the perceptually uniform color solid are not. The end user of the application chooses a new color scheme for the complete interface by repositioning the molecule within the color space. The molecule's shape and rigidity, and the space's perceptual uniformity, ensures the distinguishability and color harmony of the components are maintained. The system produces a selection of color schemes which often include subtle 'nameless' colors that people rarely choose using conventional color controls, but which blend smoothly into a harmonious color scheme. A new set of equally harmonious color schemes only requires repositioning the color molecule within the space.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Abstract: It has long been known that the post–core-collapse globular cluster M30 (NGC 7099) has a bluer-inward color gradient, and recent work suggests that the central deficiency of bright red giant stars does not fully account for this gradient. This study uses Hubble Space Telescope Wide Field Planetary Camera 2 images in the F439W and F555W bands, along with ground-based CCD images with a wider field of view for normalization of the noncluster background contribution, and finds Δ(B-V) ~ 0.3 mag for the overall cluster starlight over the range 2'' to 1' in radius. The slope of the color profile in this radial range is Δ(B-V)/Δ log r = +0.20 ± 0.07 mag dex-1, where the quoted uncertainty accounts for Poisson fluctuations in the small number of bright evolved stars that dominate the cluster light. We explore various algorithms for artificially redistributing the light of bright red giants and horizontal-branch stars uniformly across the cluster. The traditional method of redistribution in proportion to the cluster brightness profile is shown to be inaccurate. There is no significant residual color gradient in M30 after proper uniform redistribution of all bright evolved stars; thus, the color gradient in M30's central region appears to be caused entirely by post–main-sequence stars. Two classes of plausible dynamical models, Fokker-Planck and multimass King models, are combined with theoretical stellar isochrones from Bergbusch V this is consistent with M30's residual color gradient within measurement error. The observed fraction of evolved-star light in the B and V bands agrees with the corresponding model predictions at small radii but drops below it for r 20''.

Abstract: A method for preserving color information in a black and white version of a color image includes the analysis of the color image. The analysis comprises a search for conflicting colors. Conflicting colors are colors that are normally transformed to the same gray level in a black and white version of the image. One embodiment, working in a CIELAB color space includes the use of a three dimensional histogram for detecting predominant colors having the same luminance. Such colors are classified as conflicting colors. Modulations are added to the gray scale versions of conflicting colors in order to make them distinguishable. Modulation is only applied to conflicting colors thereby minimizing any deleterious effect and allowing the method to be applied in a “walk up mode” of an image processor. An image processor operative to perform the method includes an image analyzer operative to find and classify conflicting colors in the color image, and a gray scale modulator operative to add modulations to gray scale versions of only the conflicting colors within a gray scale version of the color image.

Abstract: A system and method for determining the location of human faces within a color graphics image is disclosed. The proposed method consists of several steps to distinguish face candidates from a complex background. The method determines areas with both low color gradient values and high relative intensity. These areas are then further selected on the basis of hue saturation. A final series of steps determines which of these candidate areas represent human faces within the original image.

Abstract: A morphological method for the color segmentation of cytological images is presented. This method is mainly based on watershed whose potential function blend local and global informations. The method uses a priori informations for the frame of the method. The paper is based on three parts. In a first part, the frame of a morphological segmentation method is recalled. Secondly, our morphological method of color segmentation is presented and its corresponding methodology of utilization is developped. All importants points of our morphological method are exposed : choice of the color space, choice of the color gradient, etc. Finally, the usefulness of the segmentation method is illustrated on images from serous cytology.

Abstract: An important halftoning problem faced in the design of many color printers and copiers is to represent a 24-bit color image by a small number of preset output colors, generally at a higher spatial resolution. We propose dividing the input and output image into corresponding small blocks, calculating each input block's color average, and then determining a set of the printing colors for the corresponding output block to best render the input block's average color. Our method exploits the higher spatial resolution of the printing process and yields constrained local color optimality. Artifacts common with error diffusion methods do not occur. In an experimental comparison to vector color error diffusion halftoning, block color quantization yields superior rendering of graphics. For natural images, block color quantization may occasionally generate false contours, but due to the lack of texture artifacts, block color quantization halftones may be preferable to error diffusion halftones.

Abstract: The color appearance of digital video imagery acquired from analog sources is affected by intrinsic device imperfections. Although the human visual system (HVS) is capable of perceiving color variations when comparing different acquisitions of the same video, it is able to identify the colors in an isolated image as well. Color based computer vision processes applied within digital video libraries do not have this capability and their performance is severely reduced. This paper presents a method for modeling the intrinsic color appearance given by acquisition devices. It is based on the approximation of the distribution of colors generated by a device using a mixture of Gaussians in RGB space. Its parameters are encoded in a specifically designed pattern, which provides a dense estimation of the distribution of colors along the whole RGB space. In this way, the model can be attached to every acquired video in order to put its original color appearance on record. The approximation by mixtures of Gaussians lets us define transformations between them that preserve the identity of colors. This fact is shown in the case of skin color segmentation, where the underlying concept of color is captured from samples obtained by a particular device. Other applications of color correction in digital video are pointed out in this paper as well.

Abstract: PROBLEM TO BE SOLVED: To highly accurately extract representative color from small areas on a color image and to process it at high speed for the purpose of approximating this color image. SOLUTION: The mean value and variance of respective color data inside the small area are calculated, and the color of the greatest variance is defined as a forget color. While using the mean value of this concerned color, the inside of the small area is divided into two groups. Next, area information concerning these two groups and the representative colors of the respective groups are calculated. Then, it is decided as to whether the number of provided representative colors is equal to or more than a desired color number. When the number of these colors is equal to or more than the number of the desired color, dividing processing is finished, but if the number of these colors is lacking, dividing processing is repeated again.

Abstract: The size of an uncompressed image depends on the resolution of the image and the number of colors in it. Gray-scale images typically contain 256 or fewer gray levels. In a color image, the color of each pixel is represented by three bytes, one each for red, blue and green. This leads to a potential of more than 16 million colors. However, the eye can discern only about 10,000 distinct colors. Moreover, common images usually contain fewer colors. Many images, therefore, contain much fewer colors, which form a palette. Many file formats treat the information in such a color image as a table containing the palette and individual pixels as pointers to that table. In this paper, a novel technique for hiding data using the palettes of color images is proposed. The technique can be implemented without interfering with the image data, by using unused entries or visually indistinguishable colors in the image palette.

Abstract: A data compressor compresses color difference component of pixel information converted by a converter (10). Graphics data is generated based on compressed color difference component and luminance component. Another converter (14) converts graphics data expanded by an expansion unit (13), into graphics data represented by colorimetric system. An Independent claim is also included for graphics processing method.

Abstract: The origin of color gradients in elliptical galaxies is examined by comparing model gradients with those observed in the Hubble Deep Field. The models are constructed so as to reproduce color gradients in local elliptical galaxies either by a metallicity gradient or by an age gradient. By looking-back a sequence of the color gradient as a function of redshift, the age-metallicity degeneracy is solved. The observed color gradients in elliptical galaxies at z = 0.1 to 1.0 agree excellently with those predicted by the metallicity gradient, while they deviate significantly from those predicted by the age gradient even at z ~ 0.3, and the deviation becomes larger with increasing redshift. This result does not depend on cosmological parameters and parameters for an evolutionary model of an elliptical galaxy within a reasonable range. Thus our results clearly indicate that the origin of color gradients is not age but stellar metallicity.

Abstract: This article presents a technique for detecting contours in color images based on abrupt change detections in parametric edge models. This abrupt change detection is performed on each line and column of the three component images (red, green and blue images). This technique consists in computing at each pixel a change point criterion based on a statistical change point detection. The criterion value is compared to a threshold. Two statistics models are used: the generalized likelihood ratio and the divergence statistic. The performances of these two models are about the same when applying decreasing exponential weights to the data. When there is a abrupt change on a pixel the gradient value is obtained by making the difference between the two grey-level averages on the two sides of the pixel. Finally, Di Zenzo's (1986) combination is performed in order to get the color gradient.

Abstract: Segmentation based on contour detection is a relevant stage before image interpretation or pattern recognition. This paper is concerned with color image filtering and color edge detection. These two techniques utilize the Dempster-Shafer 91968. 1976) theory. After the description of color image filtering which generalizes Nagao's (1979) filter, a method for computing the orientation and magnitude of a gradient on color images is presented. Both filtering and edge detection use a 5/spl times/5 window. Some choices in the algorithms permit one to reduce the computing complexity of evidential theory. Finally, a method which extracts the local maxima of gradient is described.