Spectral Test Instrument for Color Vision Measurement

Common displays such as CRT or LCD screens have limited capabilities in displaying most color spectra correctly. The main disadvantage of these devices is that they work with three primaries and the colors displayed are the mixture of these three colours. Consequently these devices can be confusing in testing human color identification, because the spectral distribution of the colors displayed is the combined spectrum of the three primaries. We have developed a new instrument for spectrally correct color vision measurement. This instrument uses light emitting diodes (LEDs) and is capable of producing all spectra of perceivable colors, thus with appropriate test methods this instrument can be a reliable and useful tool in test~ing human color vision and in verifying color vision correction.

Color Measurement of Segmented Printed Fabric Patterns in Lab Color Space from RGB Digital Images

Colors of textile materials are the first parameter of quality evaluated by consumers and a key component considered in selecting printed fabric. In the textiles industry, digital printed fabric analysis is one of the basic elements in successfully utilizing a color mechanism scheme and objectively evaluating fabric color alterations. Precise color measurement, however, is mostly used in sample analysis and quality inspection which help to produce reproducible or similar product. It is important that for quality inspection, the color of the product should be measured as a necessary requirement of quality control whether the product is to be accepted or not. Presented in this study is an unsupervised segmentation of printed fabrics patterns using mean shift algorithm and color measurements over the segmented regions of printed fabric patterns. The results established a consistent and reliable color measurement of multiple color patterns and appearance with the established range without any interactions.

Quantitative and Rational Research for the Sense Quantum ——Research of the Order Factors for Color Harmony Aesthetic

The paper gives a brief analysis of the color harmony aesthetic measure of Spencer which was emerged in the industry art age, and points out shortcomings of the early studies. It studies order factors which affect the color harmony aesthetic measure based on the psychophysical method, and presents a continuous curve of the order factors. These are necessary for true color CAD, and are an essential research for automatic design leading to economic and social benefits. Key words paired comparison - color harmony - aesthetic measure - order factor

Content-based Image Retrieval Using Color Histogram

This paper introduces the principles of using color histogram to match images in CBIR. And a prototype CBIR system is designed with color matching function. A new method using 2-dimensional color histogram based on hue and saturation to extract and represent color information of an image is presented. We also improve the Euclidean-distance algorithm by adding Center of Color to it. The experiment shows modifications made to Euclidean-distance signif-icantly elevate the quality and efficiency of retrieval.

Static filtering and collocation in successive steps for measurements with colored noises

The theory of static filtering in successive steps with colored noises is ample scope for its application in the procedure of GPS data processing. A majority of error and round-cycle distinctness in the measurements of GPS carrier phase can be eliminated through three times of differential calculations of stations, satellites and epochs, in which the cycle beatings became isolated values. The observation error of three-differentials in the intervals between epochs results in block diagonal matrixes in the covariance matrixes, so that the desired matrixes occupy too large memory and the processing time is too long. Therefore, by using the theory of static filtering in successive steps with colored noises, the interrelation can be eliminated and can save the processing time and memory.

2D matrix based indexing with color spectralhistogram for efficient image retrieval

A novel content based image retrieval （CBIR） algorithmusing relevant feedback is presented. The proposed frameworkhas three major contributions： a novel feature descriptor calledcolor spectral histogram （CSH） to measure the similarity betweenimages; two-dimensional matrix based indexing approach proposedfor short-term learning （STL）; and long-term learning （LTL）.In general, image similarities are measured from feature representationwhich includes color quantization, texture, color, shapeand edges. However, CSH can describe the image feature onlywith the histogram. Typically the image retrieval process starts byfinding the similarity between the query image and the imagesin the database; the major computation involved here is that theselection of top ranking images requires a sorting algorithm to beemployed at least with the lower bound of O（n log n）. A 2D matrixbased indexing of images can enormously reduce the searchtime in STL. The same structure is used for LTL with an aim toreduce the amount of log to be maintained. The performance ofthe proposed framework is analyzed and compared with the existingapproaches, the quantified results indicates that the proposedfeature descriptor is more effectual than the existing feature descriptorsthat were originally developed for CBIR. In terms of STL,the proposed 2D matrix based indexing minimizes the computationeffort for retrieving similar images and for LTL, the proposed algorithmtakes minimum log information than the existing approaches.

Review of Computer Vision Applications in Fabric Recognition and Color Analysis

Detecting various parameters of woven fabrics is one of the important methods to evaluate the quality of fabrics.In the early stage of industrial development,fabrics were mainly relied on manual to determine the quality,which was inefficient and unstable,so intelligent inspection is a popular development trend today.In recent years,computer vision technology has been widely used in the fields of fabric density measurement,color analysis,and weave pattern recognition.Based on the above three aspects,the advanced research progress of global researchers is reviewed in this paper and the shortcomings of current research and possible research directions in the future are analyzed.Computer vision technology is not only objective evaluation,but also has the advantages of accuracy and efficiency,and has a good development prospect in the field of textiles.

Temperature Measurement of Air Flow Using Fluorescent Mists Combined with Two-Color LIF

This study proposes a two-color laser-induced fluorescence (LIF) technique for measuring the temperature distribution of an airflow by spraying a mist of a fluorescent dye. The mist is generated by using propylene glycol, the vapor pressure of which is much lower than that of water, as the solvent of the fluorescent dyes. A supersonic moisture chamber is used as the atomizer for seeding the tracer particles to be visualized. The proposed technique is applied to the measurement of the temperature distribution in a thermal vertical buoyant plume. The proposed two-color LIF thermometry is found to be very effective for the study of such a thermal structure, and it is well suited for measuring the temperature field of an airflow.

New Approach for 3D Shape Measurement Based on Color-Coded Fringe and Neural Network

A new 3D surface contouring and ranging system based on digital fringe projection and phase shifting technique is presented. Using the phase-shift technique, points cloud with high spatial resolution and limited accuracy can be generated. Stereo-pair images obtained from two cameras can be used to compute 3D world coordinates of a point using traditional active triangulation approach, yet the camera calibration is crucial. Neural network is a well-known approach to approximate a nonlinear system without an explicit physical model, in this work it is used to train the stereo vision application system to calculating 3D world coordinates such that the camera calibration can be bypassed. The training set for neural network consists of a variety of stereo-pair images and the corresponding 3D world coordinates. The picture elements correspondence problem is solved by using projected color-coded fringes with different orientations. Color imbalance is completely eliminated by the new color-coded method. Once the high accuracy correspondence of 2D images with 3D points is acquired, high precision 3D points cloud can be recognized by the well trained net. The obvious advantage of this approach is that high spatial resolution can be obtained by the phase-shifting technique and high accuracy 3D object point coordinates are achieved by the well trained net which is independent of the camera model works for any type of camera. Some experiments verified the performance of the method.

Is the Two-Color Method Superior to Empirical Equations in Refractive Index Compensation?

The Edlén empirical equations and the two-color method are the commonly used approaches to converting a length measured in air to the corresponding length in vacuum to eliminate the influence of the refractive index of air. However, it is not well known whether the two-color method is superior to empirical equations in refractive index compensation. We investigated the uncertainties of these approaches via numerical calculations of their sensitivity coefficients of environmental parameters. On the basis of a comparison of their uncertainties, we found that in a 0% humidity environment, the two-color method had potential to provide greater measurement accuracy than the empirical equations.

基于二维高斯核密度估计的有色纤维颜色特征提取方法

为提高基于显微高光谱成像的有色纤维颜色测量的准确性和可重复性,研究了一种基于二维高斯核密度估计的有色纤维颜色特征提取方法。首先通过显微高光谱成像测色系统采集有色纤维的高光谱图像,选择400~700 nm、波段间隔为10 nm的光谱反射率,将其转换为色度值CIE L^(*)a^(*)b^(*),计算纤维区域中的颜色均值与每个像元颜色的色差ΔE_(00),建立色差ΔE_(00)与L^(*)相关联的二维数据;再基于二维高斯核密度估计方法计算像元的密度值,并确立了有色纤维的密度截断阈值估计方法,用于截断舍弃低密度的离散异常像元;最后根据像元的密度值计算加权光谱反射率并转换为相应的色度值。选取有色羊毛纤维进行实证分析,结果表明:影响颜色测量结果准确性和可重复性的离散异常像元主要存在于二维空间密度分布中的“尾部”区域,离散异常像元越多,“尾部”越长,对测量结果影响越严重;相比均值法和明度加权法,本文通过截断舍弃离散异常像元以减小其对测色结果影响的方式,提高了有色羊毛纤维颜色测量的准确性,且测量结果的可重复性最优,在有色羊毛纤维的染配色和混配色预测模型研究中具有实际应用价值。

不同产地与不同生产方式的丹参药材质量相似性评价研究

本研究旨在明确不同产地、不同生产方式丹参药材的质量相似性,建立丹参药材主成分特征图谱以及色差指纹图谱,形成快速、科学的立体质量评价方法,并为丹参临床使用及不同地域药材生产提供数据参考。运用HPLC建立丹参药材指纹特征图谱质量分析方法,通过中药指纹图谱相似度评价系统和ModuleLab Chroman软件对丹参药材质量进行相似性评价及计量分析;采用主成分分析(PCA)、K最近邻法(KNN)等算法及可视化方法对样品丹参药材的色度值总体分布情况进行分析。结果显示,不同产地丹参药材共有11个共有峰,合成特征图谱相似度范围为0.894~0.999,表明不同产地样品化学成分差异较小,各产地丹参药材具有较好的相似度,但根据成分PCA得分载荷图与聚类分析显示,主成分贡献率为85.93%,其中丹酚酸B成分有较高的贡献率,说明丹酚酸B是造成不同产地差异的主要物质;主成分测定显示不同产地与不同生产方式的丹参药材总丹参酮类成分也具有较大差异,总丹参酮含量为1.358~7.515 mg/g,丹酚酸B含量为4.574~112.670 mg/g;药材颜色差异分析结果表明,不同产区丹参药材颜色具有显著差异,特别是广西地区丹参药材颜色差异更加明显,模型识别率达到93.75%。本试验评价方法能快速分辨丹参药材质量差异性,可为进一步进行临床疗效评价提供数据参考,为丹参药材生产方式以及临床应用提供思路。

量子自旋调控的微位移检测系统设计与测量

以氮空位(NV)色心磁强计为基础,量子自旋调控为技术手段,结合空间梯度磁场的均匀变化,实现基于固态量子自旋的高精度微位移检测。首先,通过永磁体构建均匀变化的梯度磁场,并获得梯度磁场与位移的关联关系;其次,搭建量子自旋调控系统,并通过光探测磁共振(ODMR)确定自旋共振频点,利用拉比振荡(Rabi)确定量子调控翻转周期,完成拉姆齐(Ramsey)序列参数的测定;最后,基于Ramsey磁场测量原理,完成Ramsey所对应的荧光强度与磁场梯度变化的测试,进而实现微位移的高分辨测量,位移的最小可分辨力约为104 nm。

采用磁屏蔽环结构的金刚石NV色心全光直流互感器系统

针对目前电力系统对电流互感器的精度与灵敏度提出的更高要求,提出了一种基于金刚石氮-空位(NV)色心的全光直流互感器的系统方案,系统包括光源模块、激光反馈模块、激光分束模块、一次传感探头模块、激光分频模块、光电转换模块以及信号采集和数据处理模块。对系统中的磁屏蔽环进行了结构的设计与仿真,并对仿真结果进行了实验验证。最后搭建了单通道实验验证系统,系统实测结果表明,设计的全光直流互感器在5 000 A大电流下无磁屏蔽时可以达到0.35%的测量精度,加入磁屏蔽环后测量精度提升到了0.06%,从而为基于金刚石NV色心的全光直流互感器的研制提供了参考。

基于无微波金刚石NV色心测磁技术的电流测量应用

为了在特高压(UHV)环境下使用氮-空位(NV)色心量子测量技术,研究了金刚石主轴与磁场夹角对相应曲线及电流测量精度的影响。构建金刚石氮-空位七能级超精细结构模型,根据仿真结果得到不同磁场方向下最高灵敏度范围和最佳测量范围,从而确定探头的最佳放置角度。基于无微波金刚石氮-空位技术搭建了直流大电流测量实验平台,测试了100~5000A范围内荧光电压对电流的响应曲线。实验结果表明,该平台对5000A直流电流测量误差在0.25%以内。作为无源器件,无微波金刚石氮-空位色心测磁传感器全光纤信号传输具备良好耐压性能,同时可在室温下工作,并具有结构紧凑、灵敏度高、抗电磁干扰能力强等优势,适用于特高压环境下的直流电流测量,为传统电力行业检测提供了新的检测方法。

电网全景输电线路三维机载雷达点云信息采集研究

针对电网输电线路全景信息采集难度大、点云信息处理不准确等问题,提出了一种电网全景输电线路三维机载雷达点云信息采集系统。该系统通过对机载雷达信号处理系统设计和采集设备的选型,实现机载雷达硬件的设计和选择;采用激光雷达与惯性测量单元相结合的方式实现对输电线路点云数据更精确的采集;利用点云数据中的颜色信息和强度信息相结合的方式对点云数据进行分类处理,实现对点云数据信息的处理。通过实验验证了系统的采集误差比只采用激光雷达采集的误差小,且最大为0.21,最小为0.08;系统对不同物体的分类正确率不同,对输电线路分类正确率能达到97%,且较传统方法和单一的基于强度信息的点云数据处理分类方法正确率高。

盾构隧道钢筋混凝土管片色差影响因素分析

盾构隧道钢筋混凝土管片的色差问题愈发受到各界的关注。依据混凝土色差的形成机理,利用视觉识别手段量化混凝土管片颜色,采用单一变量法开展系列实验,通过数据分析研究了水泥化学成分、粉煤灰烧失量、混凝土坍落度、粗骨料含泥量、蒸汽养护温度几个不同因素对管片表观颜色的影响规律。针对管片色差的主要影响因素,制定了相应的施工管理措施,为管片预制工程的色差控制提供了借鉴。

基于图像识别的湿度检测

依据河北省自然科学基金“氮化碳的结构演变过程对其化学发光检测性能影响机制研究”和发明专利“湿度的检测方法及装置”的研发内容,结合颜色对湿度的水致变性,融合感光元件检测色彩信号电荷量的解算,论述了基于被测物体的图像色彩识别的湿度检测方法和测试装置的具体结构型式,为固体物体的湿度检测提供了新的解决途径。

基于HSI彩色模型远程测量青年男体围度拟合

为实现人体远程测量系统的有效性,提出运用人体照片来预测青年男体的围度。通过HSI颜色空间转换、轮廓光滑处理等图像处理方法提取了人体轮廓。通过识别人体特征点,得到人体的体表角度、宽度和厚度;按照体表角度、厚度/宽度等指标进行人体体型分类。基于各个围度对应的厚度和宽度构建了颈围、胸围、腰围、腹围、臀围和大腿根围的围度拟合方程,并对拟合方程进行了误差分析。结果表明,建立的围度预测模型有效,保证了人体远程测量系统的可靠性。

植物染散纤维色纺纱配色预测平台研究

文章针对植物染散纤维色纺纱的测配色特点,提出了在Stearns-Noechel模型中添加修正系数的计算机配色优化方案,并应用Matlab平台设计开发了相应的配色预测平台。确定了植物染散纤维色纺纱的配色模型中红、黄、蓝、白四色纤维的最佳修正系数分别为1.064、0.981、0.992、1.021,为植物染散纤维色纺纱的快速、准确配色预测提供了理论与应用基础。