Search

An object’s color depends on its reflectance and illumination, and dichromats cannot distinguish specific color pairs. It is considered that there is an appropriate illumination under which a dichromat can distinguish confusing color pairs. In this study, a fundamental investigation of an illumination transformation to assist dichromats is carried out. Because the appropriate illumination depends on the object, we propose a search algorithm for the optimum light source spectrum for an object. In experiments, the effectiveness of the proposed method is examined using digital images and an sRGB display.

Three features for image classification into natural objects and artifacts are investigated. They are 'line length ratio', 'line direction distribution,' and 'edge coverage'. Among the three, the feature 'line length ratio' shows superior classification accuracy (above 90%) that exceeds the performance of conventional features, according to experimental results in application to digital camera images. As the development of this feature was motivated by the fact that the edge sharpening magnitude in image-quality improvement must be controlled based on the image content, this classification algorithm should be especially suitable for the image-quality improvement applications.

We performed subjective experiments to evaluate color matching performance of the Spectral Properties Es- timation Model (SPEM) and six other models (von Kries, CIELAB, LLAB, RLAB, Nayatani, and CIECAM97s) be- tween two CRT monitors whose whites were quite different. Moreover, we evaluated color matching of these models between a CRT monitor and a printed image set in a dark room. The SPEM we developed is a new chromatic adap- tation model based on hypothetical spectral properties es- timation. This article describes the subjective experiments and the results obtained. The SPEM produced good color matching performance in the experiments. The detailed algorithm of the SPEM is given in the Appendix. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 445- 453, 2003; Published online in

The method of phase shift with the projection of multiple cyclic patterns enables 3D measurement that is highly accurate, dense, and fast. However, this measurement is only possible for the wrapped phase value, which has ambiguities in its multiples of cycles. Two particular problems are that conventional methods require additional patterns to be projected to determine the absolute phase and that unwrapping the phase tends to fail where depth varies abruptly. Two methods are proposed: the first is to determine the absolute phase without additional patterns being projected by observing the projected pattern with multiple cameras and applying the geometric constraints between them, and the second is to prevent failure in unwrapping the phase by referring to continuities in the relative phases of multiple projected patterns. The proposed methods were achieved with a 3D scanner that can measure approximately a 180 degrees field of view within 0.5 s, with an accuracy of 0.14 mm in depth.

Presents a head measurement system with surrounding range finders, which enables highly dense 3-D human head shape measurements to be taken quickly and precisely. Since short measurement time is as important as the inherent accuracy of instruments for measuring the human body, the system concurrently controls multiple rangefinders at video rate. It can capture all images of the human head, including the top and the chin, within a single second. Moreover, it enables measurements less than 1 mm/sup 2/ in density to be taken with average error as low as 0.4 mm. No conventional systems have both these advantages. The 3-D data acquired by the system will be utilized to design ergonomic products.

The Rainbow Range Finder (RRF) has the ability to obtain range information for all image pixels with only one frame TV camera imaging during 1/30 s. The authors propose a novel practical calibration scheme which makes range measurement for all visible pixels possible. An experimental system was developed on that basis, and measurement accuracy was evaluated. A curved surface and a plain surface could be measured with sufficient accuracy. The feasibility of a real-time system with an accuracy of 1% in regard to the measurement region size was demonstrated. >

The reproduction of natural objects in color images has attracted a great deal of attention. Reproduction more pleasing colors of natural objects is one of the methods available to improve image quality. We developed an automatic color correction method to maintain preferred color reproduction for three significant categories: facial skin color, green grass and blue sky. In this method, a representative color in an object area to be corrected is automatically extracted from an input image, and a set of color correction parameters is selected depending on the representative color. The improvement in image quality for reproductions of natural image was more than 93 percent in subjective experiments. These results show the usefulness of our automatic color correction method for the reproduction of preferred colors.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

We are developing a spectral characteristics database for evaluating color reproduction in image input devices. Thedatabase is designed so that spectral characteristics are systematically divided by category, according to the purpose to whichthey are to be applied, and every category has a sufficient variety of samples. The categories are as follows: photographicmaterials, graphic color printing, computer color printers output, paints, flowers, leaves, human skin colors and historicalKrinov data. The total number of colors is 49, 672. The database is being proposed to be published as Japanese I Interna- tional standard technical reports for use in establishing a new color reproduction evaluation method.keywords: spectral reflectance, spectral transmittance, color reproduction evaluation, image input devices, database 1. INTRODUCTION It is generally agreed that spectral sensitivities in the color sensors employed by image input devices need to satisfy theLuther condition; i.e. these sensitivities should be expressed by linear combinations of color matching functions or humancone sensitivities. For evaluating the degree to which the Luther condition is satisfied, Neugebauer's quality factor' and themeasure of goodness by Vora and Trussell2 have been proposed. However, their theory assumes that object spectral charac-teristics (reflectances and transmittances) are uniformly distributed on an entire multi-dimensional spectral vector space.Because this assumption does not hold in practice, these evaluation methods cannot be used effectively. The Luther condi-tion is only a sufficient, not a necessary, condition for good color reproduction. To overcome this problem, new methods forthe evaluation, that take the object spectral characteristics into account, are being studied3. Though such theoretical ap-proaches are important, it is difficult to deal with non-linear relations in a theory. Non-linear color mapping (e.g. artificialneural network4 etc.) for color correction is tried in many color reproduction studies. In practical sensor sensitivity design forimage input devices, real color samples (e.g. Macbeth color charts) are used to evaluate color reproduction quality. They donot have a sufficient number of colors, however, and color engineers who design input devices use arbitrary color samples.The color reproduction ability ofthe devices thus cannot be compared, since the evaluation results wholly depend on the colorsamples used.It was in response to this situation that the development of a spectral characteristics database was first proposed. Thispaper describes the above problems for color reproduction evaluation, the purposes and objectives of this database develop-ment and the database which is being developed in the following sections.

Color transformation from RGB to CMYK is a significant problem in color reproduction. Since black ink is a redundant component, it is impossible to find a unique set of CMYK ink quantity suitable for an input RGB color. This paper proposes an algorithm for UAR, using the direct color mapping method from RGB to CMYK. It directly searches a measured gamut space for a printer for more than one set of CMYK ink quantities suitable for an input color with out using a reproduction model or a nonlinear equation. A set of CMYK ink quantity, suitable for an input color, is flexibly calculated from several sets of CMYK ink quantity by using interpolation controlled by an adjusting coefficient of black ink quantity. The flexible computation of black ink quantity makes it possible to adjust a delicate image appearance. This algorithm can be applied to various kinds of printers, because it does not require a model of the printer's color reproduction mechanism.

This paper describes a new method for assisting the coloring work to achieve good color harmony in documents that contain color diagrams, figures, or images. Generally, good quality for a color document is achieved by color-element unification. Tone, a color element, is often used to arrange color harmony in a color document. A tone model is proposed that describes the color harmonization concept. An approximation formula is developed to describe the tone model. It enables simple correspondence between color coordinates and their tones. Using the tone model, users can generate a color palette that consists of colors whose subjective impression is unified. This palette is provided for coloring work, Because each of these colors has a uniform element in common, a color document, which is painted by colors from one palette, achieves the color harmonization. The tone model also provides another kind of human interface that allows the users to intuitively select a color by using the adjectives that give us the impression of color variations. Emphasis on a diagram part by selecting a color with a different tone is easily visualized. Using the prototype system, the time for coloring work was significantly reduced.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper proposes a new method for making automatic improvements in digital color imagequality. With this method, images obtained either with a video camera or by scanning photographs areautomatically enhanced on a display, and no prior knowledge is required with regard to the image datadistortions introduced by optical scanners, cameras, or transmission systems. In this paper, the featurevalues of three important factors for color image quality — image sharpness, contrast, and saturation — are defined based on human visual perception, and algorithms used for image enhancement areintroduced. The method has been experimentally applied with excellent results to the enhancementof images obtained by scanning photographs: quality improvements achieved automatically were70% of those achieved manually by human subjects. This simple, effective method appears to holdgreat promise for application to a variety of imaging devices. I INTRODUCTION The improvement in image quality is an important issue in the field of imaging systems. Inadequatepicture quality is generally the result ofdistortions introduced in the hardware —

For high-fidelity color reproduction with digital color platemaking systems, it is the most important to determine the color masking matrix which converts the red, green and blue intensities of the monitor to cyan, magenta, yellow and black inks halftone dot area rates. With regard to this determination process, the author previously developed a color difference least square method by which the optimum matrix is determined, using a simulation with the Neugebauer equation and virtual color samples. First, this paper evaluates the method with actual images. Next, the method is extended for adaptive masking matrix optimization. By adapting the matrix to each color image using black ink, it was shown that the average color differences of reproduced images could be reduced to below six when black ink is used as much as possible, i.e., in the case of achromatic printing. This masking matrix adaption is a new concept which was impossible by conventional color scanner processing, but became possible by using virtual color samples.

Automatic segmentation and classification of stained micro-organism images in micrographs are investigated. To discriminate such ellipse-like shapes, a moment based method shows higher reliability than the perimeter based method. A ‘multi-threshold-expansion algorithm’ is successfully applied to segmentation of areas which have darkly stained cores and lightly stained surroundings.

The improved LUV algorithm could highly enhance the false color image with preserved brightness and hue sensation. The resulting pictures met with approval. The algorithm was implemented as a library software and is planned to be used at Earth Resources Satellite Data Analysis Center.

Two color alteration algorithms for colorappearance simulation in design systems were developed. One algorithm is based on a surface reflection model and is suitable for plastic-like objects. Another algorithm is based on an absorption model and is suitable for transparent objects or textile-like objects. Applicability was evaluated and experiments were successful. High-speed algorithm and achromatic object coloring were also studied.

People who are engaged with computerized image processing are often worried by computer-processed results that were not anticipated. These results often occur in color displayed images. The reason is that the color difference measured in red, green, and blue (RGB) space is not perceived linearly by human eyes. The uniform color scale is adopted as an approximation to the human visual system, On this basis, data conversions are proposed that enable the matching of computer image processing to human sensing. A pseudo-color selection method and optimal color TV display characteristics are also derived from the conversion formula between the RGB and Uniform Color Scale spaces.