Effects of color display, color name, color formation and color alignment on the screen layout usability of customized product color combinations

This study investigated the effects of screen layout on the usability of a large number of color combination options for customized product. Using an L₁₈ orthogonal array, 18 interfaces were designed around four factors: color display, color name, color formation and alignment. Participants completed a color combination search task and a questionnaire concerning their satisfaction with the interfaces.Based on the search time and user satisfaction, the display of color samples by modular sections (itemized color chips) was found to be the optimal method of color selection. This arrangement reduced the number of combinations of color samples displayed on the screen and allowed efficient navigation of a large palette of color combinations. Vertical alignment aided the product color discrimination and reduced the search time. Users viewed various product color combinations directly with or without the aid of color names.

Relevance to industry

Because of the considerable observed reductions in search time and the superior reported degrees of satisfaction associated with the tested configurations for customized product color combination, the findings of this study have important ramifications for consumers and manufacturers of products as diverse as sofas, curtains, clothing, athletic shoes, cars, mobile phones and the other customized products.     

Text extraction in complex color documents

Text extraction in mixed-type documents is a pre-processing and necessary stage for many document applications. In mixed-type color documents, text, drawings and graphics appear with millions of different colors. In many cases, text regions are overlaid onto drawings or graphics. In this paper, a new method to automatically detect and extract text in mixed-type color documents is presented. The proposed method is based on a combination of an adaptive color reduction (ACR) technique and a page layout analysis (PLA) approach. The ACR technique is used to obtain the optimal number of colors and to convert the document into the principal of them. Then, using the principal colors, the document image is split into the separable color plains. Thus, binary images are obtained, each one corresponding to a principal color. The PLA technique is applied independently to each of the color plains and identifies the text regions. A merging procedure is applied in the final stage to merge the text regions derived from the color plains and to produce the final document. Several experimental and comparative results, exhibiting the performance of the proposed technique, are also presented.     

A high quality color imaging system for computerized tongue image analysis

In order to improve the quality and consistency of tongue images acquired by current imaging devices, this research aims to develop a novel imaging system which records human tongue information faithfully and precisely for medical analysis. A thorough demand analysis is firstly conducted to summarize requirements for reliable rendering of all possible medical clues, i.e., color, texture and geometric features. Then a series of system design criteria are illustrated accordingly, and by following them, three hardware modules of the imaging system, including illuminant, lighting path and imaging camera, are optimally proposed. Moreover, one built-in software module, the color correction process, is also provided to compensate color variations caused by system components. Finally, several important performance indicators, including illumination uniformity, system reproducibility and accuracy, are elaborately tested. Experimental results show that captured images are in high quality and keep stable when acquisitions are repeated. The largest color difference between any two acquired images is 1.6532, which is hardly to be distinguished by human observation. Compared to existing devices, the proposed system could provide much more accurate and stable solution for tongue image acquisition. Besides, this developed imaging system has been evaluated by doctors of Traditional Chinese Medicine for almost three years and over 9,000 tongue images have been collected, analysis results based these data also validate the effectiveness of the proposed system.     

多颜色空间取色器的设计与实现

目前常用软件使用颜色时多以RGB颜色空间为主,也有少数软件使用了HSB、Lab、CMYK等颜色空间。在肤色检测研究领域,RGB颜色空间已经满足不了研究需要,通常会采用HSI、HSV、YCbCr、YIQ、YUV等颜色空间,用于提高肤色检测的准确率和检测效率。针对常见软件的不足,给出了一款基于多颜色空间的取色器,实时抓取光标位置的颜色,并转换为HSI、HSV、YCbCr、YIQ、YUV颜色空间的表示形式,能让用户直观的看到同一颜色在不同颜色空间的各个分量值,加深用户对各种颜色的理解。     

Effects of color sample display and color sample grouping on screen layout usability for customized product color selection

This study investigates the effects of color sample display and color sample grouping on the usability (task efficiency and user preference) of a color combination interface. A 180-subject nested design experiment tested each of the three levels of color sample grouping (associative color number, color series, and product section) against each of the two levels of color sample display (color chip, product thumbnail) for efficiency and effectiveness (search time and error rate). A separate 30-subject experiment evaluated user preference.     

Color spaces and color contrast

With the introduction of low-cost color graphics systems comes a host of problems specifically concerned with the color aspect of the system. This paper discusses two of these problems: the selection and manipulation of colors by (possibly) inexperienced users, and the automatic selection of colors by the system to achieve high contrast effects on the screen. A new color space based on color opponency theory is described. This space is useful both in the user interface and in the automatic selection of high contrast colors.     

Choice of a pertinent color space for color texture characterization using parametric spectral analysis

This article presents a comparison of different color spaces including RGB, IHLS and L?a*b* for color texture characterization. This comparison is based on the fusion of the independent spatial structure and color feature cues. In IHLS and L*a*b*, two channel complex color images are created from the luminance and the chrominance values. For such images, two dimensional complex multichannel linear prediction models are used to perform parametric power spectrum estimation and the structure feature cues are computed from this estimated power spectrum. Quantitative comparison of auto spectra of luminance and combined chrominance channels for different color spaces is done. This comparison is based on the degree of decorrelation between luminance and chrominance information provided by different color space transformations. Three dimensional histograms are used as color feature cues. Then, to classify color textures, Kullback-Leibler divergence based symmetric distance measures are calculated for pure color, luminance structure and chrominance structure feature cues. Individual as well as combined effect of information from all feature cues on classification results is then compared for different color spaces and different color texture data sets. The proposed color texture classification method performs better than the state of the art methods in certain cases. The L*a*b* color space gives us a better characterization of the chrominance spatial structure as well as the overall spatial structure for all of the chosen data sets. Experimental results on pixel classification of color textures are also presented and discussed.     

A sharp edge-preserving joint color demosaicking and zooming algorithm using integrated gradients and an iterative back-projection technique

Following the advances in single-sensor imaging techniques, interest in producing a zoomed full-color image from a Bayer mosaic data has been increased. Almost all of the recent approaches identified, with respect to the demosaicking step in the imaging pipeline, have chiefly focused on misguidance problems. However, in regions consisting of sharp edges or fine textures, these approaches are prone to large blurring effects. This paper proposes a new joint solution to overcome the above problems associated with demosaicking and zooming operations. On the basis of an enhanced soft-decision framework, we estimate the edge features by computing the integrated gradients. This allows the extraction of gradient information from both color intensity and color difference domains, simultaneously. Then, the edge guidance is incorporated in the interpolation of various stages to preserve edge consistency and improve computational efficiency. In addition, an edge-adaptive, iterative, back-projection technique is developed to compensate for image blurring as well as to further suppress color artifacts. Experimental results indicate that the new algorithm produces outstanding objective performances and sharp, visually pleasing color outputs, when compared to numerous other single-sensor image zooming solutions.     

Linear color segmentation and its implementation

A framework for color image segmentation is presented, which combines color histogram analysis and region merging approach. Its main goal is to segment an image at material boundaries (i.e., discontinuities of reflectance properties) while ignoring spatial color inhomogeneities of uniformly pigmented (colored) objects, caused by accidents of illumination and viewing geometry. Theoretical examination of light spectrum transformations upon light reflection from material surfaces and upon interaction with a sensor system shows that in a wide variety of viewed scenes (even containing interreflections and highlight areas) uniformly pigmented objects are projected to the color space of the sensor as planar, linear, or point-like clusters, depending on lighting and viewing conditions and object geometry. To detect such clusters in the color space, three methods are suggested: Generalized Hough Transform method, gradient descent method, and eigenvectors method. A framework algorithm of color segmentation based on region merging approach is developed, which can use any of these methods. Testing this algorithm with both artificially generated and real images shows quite reliable results.     

A product design method for form and color matching based on aesthetic theory

Form and color matching design are vital links in product design. Recently, many scholars have focused on quantifying visual aesthetics to improve design efficiency in form or color matching design activities. However, few scholars have considered both form and color matching. Therefore, we propose a more comprehensive and practical design model based on the aesthetics theory of form and color matching. This model includes 3 phases: preparation (Phase I), form design (Phase II), and color matching design (Phase III). In Phase I, the target product's functional system and design objectives are clarified. In Phase II, the spatial layouts of the target product are analysed, and several reasonable layouts are designed in detail. Finally, the form with the highest aesthetic measurement is selected from alternatives using the modified equilibrium formula and questionnaire. In Phase III, a group of colors conforming to the target imagery is selected from a color palette. Meanwhile, a set of appropriate observation angles are chosen using an expert questionnaire. Subsequently, three-color combinations with higher color harmony are filled into images with different observation angles. Finally, the aesthetics of color matching schemes are obtained using the formula of color matching, and the scheme with a higher average value of the aesthetic measurement from all observation angles is considered the best scheme. This paper takes the fresh food vehicle and leafless fan as the cases. The best form and color matching scheme are obtained using the formula of aesthetic measurement and verified with an expert questionnaire. The result shows consistency between the results of the quantization formula and the expert questionnaire, which confirms the effectiveness of this design model. The proposed design model could improve the design efficiency and ensure the products' visual aesthetics.     

图像传感器数据插值算法的改进

当用单个图像传感器采集彩色图像时需要一个彩色滤光阵列（Color Filter Array）,这个阵列覆盖在图像传感器前面。由于彩色滤光阵列使图像传感器的每个像素只能感测一种颜色分量,所以在复原全彩色图像时必须利用颜色分量插值方法。提出了加权平均插值新算法,实验表明,新的算法比现有的几种常用插值算法有了不同程度的改善。     

浅谈用PHOTOSHOP加强色彩训练

目前有许多人想从事影视传媒行业,但大多数面临没有基础、学画时间短等问题困扰。本文从教学实践出发,针对如何培养学生的色彩感受能力、提高的表现力和色彩素养等方面进行了阐述。     

Using eigencolor normalization for illumination-invariant color object recognition

Color is one of salient features for color object recognition, however, the colors of object images sensitively depend on scene illumination. To overcome the lighting dependency problem, a color constancy or color normalization method has to be used. This paper presents a color image normalization method, called eigencolor normalization, which consists of two phases as follows. First, the compacting method, which was originally used for compensating the adverse effect due to shape distortion for 2-D planar objects, is exploited for 3-D color space to make the color distribution less correlated and more compact. Second, the compact color image is further normalized by rotating the histogram to align with the reference axis computed. Consequently, the object colors are transformed into a new color space, called eigencolor space, which reflects the inherent colors of the object and is more invariant to illumination changes. Experimental results show that our eigencolor normalization method is superior to other existing color constancy or color normalization schemes on achieving more accurate color object recognition.     

Computer artist's color naming system

A natural language based color naming system for color raster graphics, the Artist's Color Naming System (ACNS), is introduced. ACNS is an English-based nomenclature which is a high-level alternative to the numeric HSV (Hue-Saturation-Value) single-hexcone color model. ACNS suggests a grammar, based upon psychological, linguistic and artistic considerations, for constructing several hundred color designations from a small number of English terms. The ACNS twenty-four sided pyramid model and its lexicon are based upon the CNS (Color Naming System) double pyramid model and lexicon. An algorithm and a reverse algorithm for the transformation of the ACNS color space into the RGB (Red-Green-Blue) colorcube, are presented.     

Fusion of color edge detection and color quantization for color image watermarking using principal axes analysis

In the past few years, many gray-level image watermarking schemes have been proposed, although the extension to the color case is rare and regularly accomplished by marking the image luminance, or by processing each color channel separately. This paper presents a new color image watermarking scheme that combines color edge detection and color quantization using principal axes analysis in three-dimensional color space. The watermark is hidden within the data by modifying a subset of carefully selected edge points to resist both geometric distortion and signal processing attacks. Experimental results show the robustness of the proposed scheme to resist common attacks.     

基于三维色立体的计算机辅助色彩设计*

通过分析现有色彩设计工具的研究现状和不足,提出了一套基于色立体的产品色彩设计策略。讨论了相关的关键技术：基于可视化色彩模型的自由选色;色立体调和规则功能函数实现的色彩调和;与色立体对应的色彩语义配置;体现色立体信息特征的色彩方案库构建与管理。基于上述策略和技术开发了基于三维色立体的计算机辅助色彩设计系统框架。     

Tutorial on color science

The principles of tristimulus colorimetry are presented in tutorial fashion. The classic color matching experiments are described with an emphasis on the assumptions that are implicit in these tests and on the units of measure which should be used to record the results. The transformation to alternative sets of primaries is derived and the geometry of the resulting color spaces is illustrated. An annotated bibliography of relevant literature is also provided.