WO2022110583A1 - 一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法及应用 - Google Patents

一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法及应用 Download PDF

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WO2022110583A1
WO2022110583A1 PCT/CN2021/082614 CN2021082614W WO2022110583A1 WO 2022110583 A1 WO2022110583 A1 WO 2022110583A1 CN 2021082614 W CN2021082614 W CN 2021082614W WO 2022110583 A1 WO2022110583 A1 WO 2022110583A1
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color
fiber
dimensional
primary color
grid point
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薛元
崔鹏
孙显强
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Jiangnan University
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • D—TEXTILES; PAPER
    • D02—YARNS; MECHANICAL FINISHING OF YARNS OR ROPES; WARPING OR BEAMING
    • D02G—CRIMPING OR CURLING FIBRES, FILAMENTS, THREADS, OR YARNS; YARNS OR THREADS
    • D02G3/00—Yarns or threads, e.g. fancy yarns; Processes or apparatus for the production thereof, not otherwise provided for
    • D02G3/22—Yarns or threads characterised by constructional features, e.g. blending, filament/fibre
    • D02G3/34—Yarns or threads having slubs, knops, spirals, loops, tufts, or other irregular or decorative effects, i.e. effect yarns
    • D02G3/346—Yarns or threads having slubs, knops, spirals, loops, tufts, or other irregular or decorative effects, i.e. effect yarns with coloured effects, i.e. by differential dyeing process
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G06F16/5838—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using colour
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30124—Fabrics; Textile; Paper
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

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  • the invention relates to a color fiber multi-dimensional color mixing space grid model and a grid point array color matrix construction method and application, and belongs to the technical field of color space grid construction.
  • Color fibers with different color effects can be obtained by technical means such as dyeing of textile fiber materials, dope dyeing, biological transgenic, and structural color generation.
  • Colored colored yarns in theory, the basic color, blending ratio, blending method, and the structure of the forming yarns of the blended fibers have a great influence on the hue, lightness and saturation of the colored yarns, but in the actual production process, usually Based on a certain color mixing method and yarn structure, the selection of the basic color of the colored fiber and the selection of the color mixing ratio are mainly considered.
  • the production of colored spun yarn needs to complete the color design, specification design and spinning process design of the colored spun yarn.
  • the color design of color spinning there are usually the following five workflows: (1) Innovate the color of the yarn based on the existing color system, and develop the colored yarn. At this time, it is necessary to make different combinations of several colored fibers in the library and select different proportions for mixed color spinning, and select several color schemes from the trial-spun serialized colored yarns as new products for market promotion; (2) Based on popular colors or Designers personally prefer to select color systems to innovate in yarn colors and develop colored yarns.
  • the designer selects several groups of basic color systems for fiber dyeing according to his own understanding and imagination of color, and combines several groups of color fibers selected by the designer in different combinations and selects different proportions for mixed color spinning.
  • determine which kinds of colored fibers are used for mixed color spinning in what proportion? Send the sample of the trial-spun colored yarn to the customer for confirmation, and determine the color scheme of the colored yarn after several rounds.
  • the core technology of producing colored yarn or colored yarn is to optimize the color scheme of colored yarn, whether it is based on the existing color system for yarn color innovation, or based on the designer's personal preference to select the color system for yarn color innovation, or based on the existing color system.
  • For color reproduction it is necessary to be familiar with the changing laws of color hue, lightness and saturation, to be sensitive to the subtle differences between colors, and to master the color matching skills of colored yarns.
  • the design of the color scheme mainly relies on the designer's personal experience and intuition.
  • the completion of the color matching process mainly relies on manual sample making, manual dyeing, and manual color matching.
  • the evaluation of the color matching results mainly relies on the observation of the physical samples on the spot and the subjective feeling. Evaluate.
  • the color mixing process of colored fibers is the color mixing process, which belongs to the space juxtaposition of color mixing.
  • the color mixing process of color fibers is the color mixing process of color materials.
  • the traditional color matching method does not establish a digital physical model to express the color mixing process of color fibers. It is necessary to build a physical model and digitally express the color mixing process of color fibers;
  • the color mixing process of colored fibers is to select several colored fibers as the basic colors, and obtain a serialized color spectrum by changing the blending ratio.
  • the traditional color matching method produces mixed color samples by hand proofing, and there is no digital method to obtain the color value of the mixed color body based on the color value of the base color and the change of the mixed color ratio.
  • Digital virtual color matching
  • Serialized chromatograms can be obtained through the color matching process of colored fibers.
  • the traditional color matching method is obtained by manual proofing, which is inefficient, time-consuming, and inconvenient for remote transmission. It is necessary to construct a standard color mixing chromatogram for the combination of eight primary colors such as red, green, blue, cyan, blue, magenta, black, and white to provide a reference for the color matching of colored yarns;
  • the technical problem to be solved by the present invention is to provide a multi-dimensional color mixing space grid model of color fibers and a method for constructing a grid point array color matrix.
  • a coordinate digital quantization process is introduced to realize the visualization of colors in the multi-primary RGB color space.
  • the present invention designs a multi-dimensional color mixing space grid model of color fibers and a method for constructing a color matrix of grid point arrays.
  • the multi-dimensional coordinate system is based on the fiber quality of each primary color corresponding to each coordinate axis in the multi-dimensional coordinate system to realize the construction of the multi-dimensional color mixing grid model and grid point array color matrix, including the following steps:
  • Step C The mixing ratios ⁇ m ( i 1 , . . . , im , .
  • ⁇ m (i 1 ,...,im ,...,i M ) [ ⁇ m *(i m -1)/ n m ] /[ ⁇ 1 *(i 1 -1)/n 1 +...+ ⁇ m *(i m -1)/n m +...+ ⁇ M *(i M -1)/n M ];
  • Step D The quality model of any grid point in the cube space corresponding to the preset maximum quality of each primary color fiber corresponding to the multi-dimensional color mixing space grid model is constructed as follows, and then proceed to step E;
  • ⁇ ⁇ (i 1 ,...,im ,...,i M ) [ ⁇ 1 *(i 1 -1)/n 1 +...+ ⁇ m *(im -1)/ n m + ...+ ⁇ M *(i M -1)/n M ];
  • im 1,..., n m +1 ;
  • Step E The quality matrix of any grid point in the cube space corresponding to the multi-dimensional color mixing space grid model based on the preset maximum quality of each primary color fiber is as follows, and then enter step F;
  • im 1,..., n m +1 ;
  • Step F The color value model of any grid point in the cube space corresponding to the preset maximum quality of each primary color fiber corresponding to the multi-dimensional color mixing space grid model is as follows:
  • step G wherein R 1 , G 1 , and B 1 represent the RGB color values corresponding to the first primary color fiber, R m , G m , and B m represent the RGB color values corresponding to the m-th primary color fiber, and R M , GM , and BM represent the RGB color values corresponding to the M-th primary color fiber,
  • R ⁇ (i 1 ,...,im ,...,i M ) in the multi-dimensional coordinate system R ⁇ (i 1 ,...,im ,..., i M ), G ⁇ (i 1 ,...,im ,...,i M ), B ⁇ (i 1 ,...,im ,..., i M ) represent coordinates ( i 1 ,...,im ,..., i M ) the RGB color value of each base-color fiber mixed yarn corresponding to the position;
  • Step G The color value matrix of any grid point in the cube space based on the preset maximum quality of each primary color fiber corresponding to the multi-dimensional color mixing space grid model is as follows:
  • step A based on the fact that the maximum mass and equal fraction of each primary color fiber are equal to each other, that is, the ⁇ m corresponding to each primary color fiber is equal to each other, and the n m corresponding to each primary color fiber is equal to each other, then step A
  • the color value model of any grid point in the cube space based on the preset maximum quality of each primary color fiber corresponding to the multi-dimensional color mixing space grid model obtained in step G is as follows:
  • any K parameters based on (i 1 ,...,im ,...,i M ) are variables, and the remaining parameters are constants, respectively . against Construct (n m +1) MK (n m +1) K -dimensional multidimensional color arrays, where 1 ⁇ K ⁇ M.
  • the present invention designs an application of a multi-dimensional color mixing space grid model for color fibers and a method for constructing a color matrix of a grid point array.
  • the color value of any grid point in the cube space of is stored in the database, and is used to analyze the target color as follows;
  • the preferred detection is to obtain the RGB color detection data corresponding to the target color, and find the grid point corresponding to the RGB color detection data in the database; In the method, the grid point corresponding to the target color is obtained; finally, the RGB color data corresponding to the target color is formed from the RGB color data corresponding to the grid point.
  • a color detector is used to detect the target color, and the RGB color detection data corresponding to the target color is obtained.
  • a color fiber multi-dimensional color mixing space grid model and a grid point array color matrix construction method and application described in the present invention using the above technical solution compared with the prior art, has the following technical effects:
  • the multi-dimensional color mixing space grid model of the color fiber and the construction method and application of the color matrix of the grid point array designed by the present invention for specifying each primary color fiber, the coordinate digital quantization process is introduced, and each primary color fiber corresponds to each coordinate axis of the multi-dimensional coordinate system.
  • the mixed yarn object of each primary color fiber is obtained from each grid point in the multi-dimensional coordinate system space, thereby combining the mixing ratio of each primary color fiber and the RGB color of each primary color fiber , to realize the RGB color modeling of the mixed yarn object, that is, to form a multi-dimensional color mixing grid model and a grid point array color matrix, and thus further realize the construction of a line array model, an area array model, and a volume array model.
  • the RGB color space under fiber mixing realizes digital quantization, and can call each group of models arbitrarily in practical applications to realize color visualization, which effectively improves the efficiency of color analysis and selection.
  • FIG. 1 is a schematic flowchart of a multi-dimensional color mixing space grid model for color fibers designed by the present invention and a method for constructing a grid point array color matrix.
  • the invention designs a multi-dimensional color mixing space grid model of color fibers and a method for constructing a color matrix of grid point arrays.
  • the quality of each primary color fiber corresponds to
  • Each coordinate axis in the multi-dimensional coordinate system realizes the construction of a multi-dimensional color mixing grid model and a grid point array color matrix.
  • the following steps A to G are performed.
  • Step C The mixing ratios ⁇ m ( i 1 , . . . , im , .
  • ⁇ m (i 1 ,...,im ,...,i M ) [ ⁇ m *(i m -1)/ n m ] /[ ⁇ 1 *(i 1 -1)/n 1 +...+ ⁇ m *(i m -1)/n m +...+ ⁇ M *(i M -1)/n M ].
  • Step D The quality model of any grid point in the cube space corresponding to the preset maximum quality of each primary color fiber corresponding to the multi-dimensional color mixing space grid model is constructed as follows, and then proceed to step E;
  • ⁇ ⁇ (i 1 ,...,im ,...,i M ) [ ⁇ 1 *(i 1 -1)/n 1 +...+ ⁇ m *(im -1)/ n m + ...+ ⁇ M *(i M -1)/n M ];
  • Step E The quality matrix of any grid point in the cube space corresponding to the multi-dimensional color mixing space grid model based on the preset maximum quality of each primary color fiber is as follows, and then enter step F;
  • Step F The color value model of any grid point in the cube space corresponding to the preset maximum quality of each primary color fiber corresponding to the multi-dimensional color mixing space grid model is as follows:
  • step G wherein R 1 , G 1 , and B 1 represent the RGB color values corresponding to the first primary color fiber, R m , G m , and B m represent the RGB color values corresponding to the m-th primary color fiber, and R M , GM , and BM represent the RGB color values corresponding to the M-th primary color fiber,
  • R ⁇ (i 1 ,...,im ,...,i M ) in the multi-dimensional coordinate system R ⁇ (i 1 ,...,im ,..., i M ), G ⁇ (i 1 ,...,im ,...,i M ), B ⁇ (i 1 ,...,im ,..., i M ) represent coordinates ( i 1 ,...,im ,..., i M )
  • Step G The color value matrix of any grid point in the cube space corresponding to the preset maximum quality of each primary color fiber corresponding to the multi-dimensional color mixing space grid model is as follows:
  • the multi-dimensional color mixing space obtained from step A to step G The color value model of any grid point in the cube space corresponding to the preset maximum quality of each primary color fiber corresponding to the grid model is as follows:
  • n m corresponding to each primary color fiber are equal to each other, wherein any K parameters based on (i 1 ,...,im ,...,i M ) are variables respectively, and the remaining parameters are constants respectively .
  • the present invention designs an application for a multi-dimensional color mixing space grid model of color fibers and a method for constructing a color matrix of a grid point array.
  • the color value of any grid point in the cube space with the preset maximum quality of the primary color fiber is stored in the database, and is used to analyze the target color in the following way;
  • a color detector to detect the RGB color detection data corresponding to the target color, and find the grid point corresponding to the RGB color detection data in the database; The grid point corresponding to the target color is obtained by means of comparison; finally, the RGB color data corresponding to the target color is formed from the RGB color data corresponding to the grid point.
  • the quality of fiber ⁇ is divided into 10 equal parts, the quality of color fiber ⁇ is divided into 10 equal parts, and the quality of color fiber ⁇ is divided into 10 equal parts, and weights are carried out according to the arithmetic sequence to obtain the mixture ⁇ ⁇ . Expand the mixture ⁇ ⁇ along the axis of the point ⁇ , and 11 11*11 surface matrices can be obtained. The corresponding RGB values are shown in the color comparison table. The color comparison of the color fiber three-dimensional grid color mixing matrix is shown in Table 1 below. surface.
  • the color value is ⁇ (0,255,255), ⁇ (255,0,255), ⁇ (255,255,0), ⁇ (0,0,0), respectively divide the weight of color fiber ⁇ into 10 equal parts, and the weight of color fiber ⁇ Divide into 10 equal parts, the weight of color fiber ⁇ is divided into 4 equal parts, and the weight of color fiber ⁇ is divided into 4 equal parts, and weight is carried out according to the arithmetic sequence to obtain the mixture ⁇ ⁇ . Expand the mixture ⁇ ⁇ along the surface where point ⁇ and point ⁇ are located, and 25 surface matrices of 11*11 can be obtained.
  • the corresponding RGB values are shown in the color comparison table, as shown in the following table 2.
  • the weight of ⁇ is divided into 10 equal parts, the weight of color fiber ⁇ is divided into 10 equal parts, the weight of color fiber ⁇ is divided into 4 equal parts, the weight of color fiber ⁇ is divided into 4 equal parts, and the weight of color fiber ⁇ is divided into 4 equal parts.
  • the arithmetic sequence is weighted to obtain the mixture ⁇ ⁇ . Expand the mixture ⁇ ⁇ along the surface where the point ⁇ and the point ⁇ are located, and 125 surface matrices of 11*11 can be obtained. Only the first three and the last three are listed here, and the other 119 surface matrices can be discussed as above.
  • the obtained surface array matrix is calculated, and its corresponding RGB values are shown in the color comparison table, as shown in Table 3 below for the color comparison table of the color fiber five-dimensional grid color mixing matrix.

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Abstract

一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法及应用，针对指定各基色纤维，引入坐标数字量化过程，将各基色纤维分别对应于多维坐标系的各坐标轴，以基色纤维参与混合的质量作为坐标轴数据，由多维坐标系空间的各个网格点获得各基色纤维的混合纱线对象，由此结合各基色纤维的混合比，以及各基色纤维的RGB颜色，实现对混合纱线对象的RGB颜色建模，即构成多维混色空间网格模型及网格点阵列颜色矩阵，并由此进一步实现线阵列模型、面阵列模型、体阵列模型的构建，针对多基色纤维混合下的RGB颜色空间实现了数字量化，能够在实际应用中任意调用各组模型实现颜色的可视化，有效提高了颜色分析、选择的效率。

Description

一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法及应用 技术领域
本发明涉及一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法及应用，属于颜色空间网格构建技术领域。
背景技术
通过对纺织纤维材料的染色、原液着色、生物转基因、结构生色等技术手段可获取具有不同色彩效应的彩色纤维，将多种不同色彩的纤维按照某种比例进行混色纺纱可得到具有某种色彩的色纺纱，理论上混纺纤维的基色、混和比例、混和方式、成型纱线的结构等因素对色纺纱色相、明度及饱和度都有较大影响，但在实际生产过程中，通常以某种混色方式和成纱结构为基础，重点考虑彩色纤维基色的选择及其混色比例的选择。利用多元基色的染色纤维或者原液着色纤维混色纺制色纺纱，并通过变动基色纤维的比例调控色纺纱的色相、明度及饱和度，是设计并实现色纺纱的必要手段。
生产色纺纱需要完成色纺纱的色彩设计、规格设计、纺纱工艺设计。在进行色纺纱色彩设计时，通常有以下五种工作流程：(1)基于现有色系进行纱线色彩创新，开发彩色纱线。此时需要将在库的若干彩色纤维进行不同组合并选用不同比例进行混色纺纱，从试纺的系列化彩色纱线中选择几个配色方案作为新品进行市场推广；(2)基于流行色或设计师个人喜好选定色系进行纱线色彩创新，开发彩色纱线。此时由设计师根据自己对色彩的理解和想象选择几组基础色系进行纤维染色，将设计师选定的几组彩纤维进行不同组合并选用不同比例进行混色纺纱，从试纺的系列化彩色纱线中选择几个配色方案作为新品进行市场推广；(3)基于来样进行色彩复制，开发彩色纱线。在分析来样的基础上，确定采用哪几种彩色纤维按照何种比例进行混色纺纱？将试纺色纺纱样交客户确认，经若干回合后确定色纺纱配色方案。
生产色纺纱或彩色纱的核心技术是优选彩色纱的配色方案，无论是基于现有色系进行纱线色彩创新，还是基于设计师个人喜好选定色系进行纱线色彩创新，或是基于来样进行色彩复制，都需要熟悉色彩色相、明度及饱和度的变化规律，敏感察觉色彩之间的微妙差异，掌握彩色纱线的配色技巧。
当前，配色方案的设计主要依靠设计师个人的经验和直觉进行，配色过程的完成主要依靠手工制样、手工染色、手工配色，配色结果的评价主要依靠在现场对实物样的观察，依托主观感受进行评价。彩色纤维的混色过程是色料混色过程，属于色彩的空间并置混色。
现有色彩体系中的颜色可通过颜色空间中的R、G、B值进行标定，因此任一颜色都可用颜色空 间的某个向量表示。如果将颜色a(R a、G a、B a)、b(R b、G b、B b)、b(R b、G b、B b)、d(R d、G d、B d、e(R e、G e、B e)混色可得到混色样的颜色值m(R m、G m、B m)，则混色样的颜色值R m＝R a+R b+R c+R d+R e、G m＝G a+G b+G c+G d+G e、B m＝B a+B b+B c+B d+B e，相当于颜色空间中求向量之和的运算。既然色彩及色彩的混色均可数字化表达，所以也可对彩色纤维的混色过程进行数字化表达。基于上述分析，我们认为传统配色方法主要存在以下问题：
1、彩色纤维的混色过程是色料混色过程，传统配色方法未建立数字化的物理模型对彩色纤维的混色过程进行表达，需要构建物理模型并对彩色纤维的混色过程进行数字化表达；
2、彩色纤维的混配色过程，就是选择几种彩色纤维作为基础颜色，通过变化混纺比得到系列化的色谱。传统配色方法通过手工打样制作混色样品，未建立基于基色颜色值以及混色比例变化求取混色体颜色值的数字化方法，需要构建彩色纤维离散混色模型及其混色色谱的可视化算法，实现彩色纱线的数字化虚拟配色；
3、通过彩色纤维的配色过程可以得到系列化色谱。传统配色方法采用手工打样获取，获取配色色谱效率低、耗时长、不便于远程传输。需要构建红、绿、蓝、青、蓝、品红、黑、白等八基色纤维组合混配的标准混色色谱，为彩色纱线的配色提供参考依据；
发明内容
本发明所要解决的技术问题是提供一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法，针对指定各基色纤维，引入坐标数字量化过程，实现多基色RGB颜色空间颜色的可视化。
本发明为了解决上述技术问题采用以下技术方案：本发明设计了一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法，针对指定各基色纤维，以及维度数与基色纤维数相等的多维坐标系，以各基色纤维质量分别对应多维坐标系中的各根坐标轴，实现多维混色网格模型及网格点阵列颜色矩阵的构建，包括如下步骤：
步骤A.根据各基色纤维别所对应的预设最大质量ω m，确定各基色纤维最大质量分别所对应其所设坐标轴的位置，然后进入步骤B；其中，m＝{1、…、M}，M表示基色纤维的数目，ω m表示第m根基色纤维别所对应的预设最大质量；
步骤B.分别针对多维坐标系中原点与各根坐标轴上相应基色纤维最大质量位置之间的线段，执行n m等分，获得该线段上各点的质量
Figure PCTCN2021082614-appb-000001
i m＝1、…、n m+1，i m表示第m根基色纤维所对 应坐标轴线段上、由多维坐标系中原点至相应基色纤维最大质量位置方向各点的序号；n m表示针对第m根基色纤维所对应坐标轴上线段执行的等分数；然后进入步骤C；
步骤C.构建多基色纤维分别所对应的混合比λ m(i 1,…,i m,…,i M)如下，然后进入步骤D；
λ m(i 1,…,i m,…,i M)＝[ω m*(i m-1)/n m]/[ω 1*(i 1-1)/n 1+…+ω m*(i m-1)/n m+…+ω M*(i M-1)/n M]；
步骤D.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的质量模型如下，然后进入步骤E；
ω ξ(i 1,…,i m,…,i M)＝[ω 1*(i 1-1)/n 1+…+ω m*(i m-1)/n m+…+ω M*(i M-1)/n M]；
其中，i m＝1、…、n m+1；
步骤E.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的质量矩阵如下，然后进入步骤F；
Figure PCTCN2021082614-appb-000002
其中，i m＝1、…、n m+1；
步骤F.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值模型如下：
Figure PCTCN2021082614-appb-000003
然后进入步骤G，其中，R 1、G 1、B 1表示第1根基色纤维所对应的RGB颜色值，R m、G m、B m表示第m根基色纤维所对应的RGB颜色值，R M、G M、B M表示第M根基色纤维所对应的RGB颜色值，
Figure PCTCN2021082614-appb-000004
表示多维坐标系中坐标(i 1,…,i m,…,i M)位置所对应各基色纤维混合纱线的颜色值，R ξ(i 1,…,i m,…,i M)、G ξ(i 1,…,i m,…,i M)、B ξ(i 1,…,i m,…,i M)表示多维坐标系中坐标(i 1,…,i m,…,i M)位置所对应各基色纤维混合纱线的RGB颜色值；
步骤G.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意 网格点的颜色值矩阵如下：
Figure PCTCN2021082614-appb-000005
其中，i m＝1、…、n m+1。
作为本发明的一种优选技术方案：基于所述各基色纤维的最大质量与等分数就彼此相等，即各基色纤维对应的ω m彼此相等，各基色纤维对应的n m彼此相等，则步骤A至步骤G所获多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值模型如下：
Figure PCTCN2021082614-appb-000006
作为本发明的一种优选技术方案：基于步骤A至步骤G所获多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值模型，以及各基色纤维对应的ω m彼此相等，各基色纤维对应的n m彼此相等，其中，基于(i 1,…,i m,…,i M)中任意K个参数分别为变量，其余参数分别为常数，针对
Figure PCTCN2021082614-appb-000007
构建(n m+1) M-K个(n m+1) K维的多维颜色阵列，其中，1≤K≤M。
与上述相对应，本发明设计一种针对彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法的应用，将所述多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值，存储于数据库中，按如下方式，用于实现对目标颜色的分析；
首选检测获得目标颜色所对应的RGB颜色检测数据，并在数据库中查找该RGB颜色检测数据所对应的网格点；然后在以该网格点为原点、周围预设半径范围，通过比对的方式，获得目标颜色所对应的网格点；最后由该网格点所对应的RGB颜色数据，构成目标颜色所对应的RGB颜色数据。
作为本发明的一种优选技术方案：采用检色仪针对目标颜色进行检测，获得目标颜色所对应的RGB颜色检测数据。
本发明所述一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法及应用，采用以上技术方案与现有技术相比，具有以下技术效果：
本发明所设计彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法及应用，针对指定各基色纤维，引入坐标数字量化过程，将各基色纤维分别对应于多维坐标系的各坐标轴，以基色 纤维参与混合的质量作为坐标轴数据，由多维坐标系空间的各个网格点获得各基色纤维的混合纱线对象，由此结合各基色纤维的混合比，以及各基色纤维的RGB颜色，实现对混合纱线对象的RGB颜色建模，即构成多维混色网格模型及网格点阵列颜色矩阵，并由此进一步实现线阵列模型、面阵列模型、体阵列模型的构建，针对多基色纤维混合下的RGB颜色空间实现了数字量化，能够在实际应用中任意调用各组模型实现颜色的可视化，有效提高了颜色分析、选择的效率。
附图说明
图1是本发明所设计彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法流程示意图。
具体实施方式
下面结合说明书附图对本发明的具体实施方式作进一步详细的说明。
本发明设计了一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法，针对指定各基色纤维，以及维度数与基色纤维数相等的多维坐标系，以各基色纤维质量分别对应多维坐标系中的各根坐标轴，实现多维混色网格模型及网格点阵列颜色矩阵的构建，如图1所示，执行如下步骤A至步骤G。
步骤A.根据各基色纤维别所对应的预设最大质量ω m，确定各基色纤维最大质量分别所对应其所设坐标轴的位置，然后进入步骤B；其中，m＝{1、…、M}，M表示基色纤维的数目，ω m表示第m根基色纤维别所对应的预设最大质量。
步骤B.分别针对多维坐标系中原点与各根坐标轴上相应基色纤维最大质量位置之间的线段，执行n m等分，获得该线段上各点的质量
Figure PCTCN2021082614-appb-000008
i m＝1、…、n m+1，i m表示第m根基色纤维所对应坐标轴线段上、由多维坐标系中原点至相应基色纤维最大质量位置方向各点的序号；n m表示针对第m根基色纤维所对应坐标轴上线段执行的等分数；然后进入步骤C。
步骤C.构建多基色纤维分别所对应的混合比λ m(i 1,…,i m,…,i M)如下，然后进入步骤D；
λ m(i 1,…,i m,…,i M)＝[ω m*(i m-1)/n m]/[ω 1*(i 1-1)/n 1+…+ω m*(i m-1)/n m+…+ω M*(i M-1)/n M]。
步骤D.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的质量模型如下，然后进入步骤E；
ω ξ(i 1,…,i m,…,i M)＝[ω 1*(i 1-1)/n 1+…+ω m*(i m-1)/n m+…+ω M*(i M-1)/n M]；
其中，i m＝1、…、n m+1。
步骤E.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的质量矩阵如下，然后进入步骤F；
Figure PCTCN2021082614-appb-000009
其中，i m＝1、…、n m+1。
步骤F.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值模型如下：
Figure PCTCN2021082614-appb-000010
然后进入步骤G，其中，R 1、G 1、B 1表示第1根基色纤维所对应的RGB颜色值，R m、G m、B m表示第m根基色纤维所对应的RGB颜色值，R M、G M、B M表示第M根基色纤维所对应的RGB颜色值，
Figure PCTCN2021082614-appb-000011
表示多维坐标系中坐标(i 1,…,i m,…,i M)位置所对应各基色纤维混合纱线的颜色值，R ξ(i 1,…,i m,…,i M)、G ξ(i 1,…,i m,…,i M)、B ξ(i 1,…,i m,…,i M)表示多维坐标系中坐标(i 1,…,i m,…,i M)位置所对应各基色纤维混合纱线的RGB颜色值。
步骤G.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值矩阵如下：
Figure PCTCN2021082614-appb-000012
其中，i m＝1、…、n m+1。
进一步，基于所述各基色纤维的最大质量与等分数就彼此相等，即各基色纤维对应的ω m彼此相等，各基色纤维对应的n m彼此相等，则步骤A至步骤G所获多维混色空间网格模型所对应基于各基 色纤维预设最大质量的立方体空间中任意网格点的颜色值模型如下：
Figure PCTCN2021082614-appb-000013
此外，基于步骤A至步骤G所获多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值模型，以及各基色纤维对应的ω m彼此相等，各基色纤维对应的n m彼此相等，其中，基于(i 1,…,i m,…,i M)中任意K个参数分别为变量，其余参数分别为常数，针对
Figure PCTCN2021082614-appb-000014
构建(n m+1) M-K个(n m+1) K维的多维颜色阵列，其中，1≤K≤M。
实际应用当中，与上述设计方法相对应，本发明设计一种针对彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法的应用，将所述多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值，存储于数据库中，按如下方式，用于实现对目标颜色的分析；
首选采用检色仪检测获得目标颜色所对应的RGB颜色检测数据，并在数据库中查找该RGB颜色检测数据所对应的网格点；然后在以该网格点为原点、周围预设半径范围，通过比对的方式，获得目标颜色所对应的网格点；最后由该网格点所对应的RGB颜色数据，构成目标颜色所对应的RGB颜色数据。
将本发明所设计彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法及应用，应用于实际当中，诸如针对三维混色网格颜色空间网格点阵列模型的构建，假设三元彩纤α、β、γ的质量分别为ω α＝10、ω β＝10、ω γ＝10，颜色值为α(0,255,255)、β(255，0,255)、γ(255,255,0)，分别将彩纤α的质量分成10等分，彩纤β的质量分成10等分，彩纤γ的质量分成10等分，并按等差数列进行配重，得到混合体ω ξ。将混合体ω ξ沿着点γ所在的轴展开，可得11个11*11的面矩阵，其对应的RGB值见颜色对照表，如下表1所示彩色纤维三维网格混色矩阵的颜色对照表。
表1
p＝1 1 2 3 4 5 6 7 8 9 10 11
1 0,255,255 23,232,255 43,213,255 59,196,255 73,182,255 85,170,255 96,159,255 105,150,255 113,142,255 121,134,255 128,128,255
2 0,255,255 26,230,255 46,209,255 64,191,255 78,177,255 91,164,255 102,153,255 112,143,255 120,135,255 128,128,255 134,121,255
3 0,255,255 28,227,255 51,204,255 70,185,255 85,170,255 98,157,255 109,146,255 119,136,255 128,128,255 135,120,255 142,113,255
4 0,255,255 32,223,255 57,198,255 77,179,255 93,162,255 106,149,255 118,137,255 128,128,255 136,119,255 143,112,255 150,105,255
5 0,255,255 36,219,255 64,191,255 85,170,255 102,153,255 116,139,255 128,128,255 137,118,255 146,109,255 153,102,255 159,96,255
6 0,255,255 43,213,255 73,182,255 96,159,255 113,142,255 128,128,255 139,116,255 149,106,255 157,98,255 164,91,255 170,85,255
7 0,255,255 51,204,255 85,170,255 109,146,255 128,128,255 142,113,255 153,102,255 162,93,255 170,85,255 177,78,255 182,73,255
8 0,255,255 64,191,255 102,153,255 128,128,255 146,109,255 159,96,255 170,85,255 179,77,255 185,70,255 191,64,255 196,59,255
9 0,255,255 85,170,255 128,128,255 153,102,255 170,85,255 182,73,255 191,64,255 198,57,255 204,51,255 209,46,255 213,43,255
10 0,255,255 128,128,255 170,85,255 191,64,255 204,51,255 213,43,255 219,36,255 223,32,255 227,28,255 230,26,255 232,23,255
11 255,255,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255
诸如针对四维混色网格颜色空间网格点阵列模型的构建，假设四元彩纤α、β、γ、δ的重量分别为ω α＝10、ω β＝10、ω γ＝10、ω δ＝10，颜色值为α(0,255,255)、β(255，0,255)、γ(255,255,0)、δ(0,0,0)，分别将彩纤α的重量分成10等分，彩纤β的重量分成10等分，彩纤γ的重量分成4等分，彩纤δ的重量分成4等分，并按等差数列进行配重，得到混合体ω ξ。将混合体ω ξ沿着点α、点β所在的面展开，可得25个11*11的面矩阵，其对应的RGB值见颜色对照表，如下表2所示彩色纤维四维网格混色矩阵的颜色对照表。
表2
[ξ i,j,1,1] 1 2 3 4 5 6 7 8 9 10 11
1 0,255,255 23,232,255 43,213,255 59,196,255 73,182,255 85,170,255 96,159,255 105,150,255 113,142,255 121,134,255 128,128,255
2 0,255,255 26,230,255 46,209,255 64,191,255 78,177,255 91,164,255 102,153,255 112,143,255 120,135,255 128,128,255 134,121,255
3 0,255,255 28,227,255 51,204,255 70,185,255 85,170,255 98,157,255 109,146,255 119,136,255 128,128,255 135,120,255 142,113,255
4 0,255,255 32,223,255 57,198,255 77,179,255 93,162,255 106,149,255 118,137,255 128,128,255 136,119,255 143,112,255 150,105,255
5 0,255,255 36,219,255 64,191,255 85,170,255 102,153,255 116,139,255 128,128,255 137,118,255 146,109,255 153,102,255 159,96,255
6 0,255,255 43,213,255 73,182,255 96,159,255 113,142,255 128,128,255 139,116,255 149,106,255 157,98,255 164,91,255 170,85,255
7 0,255,255 51,204,255 85,170,255 109,146,255 128,128,255 142,113,255 153,102,255 162,93,255 170,85,255 177,78,255 182,73,255
8 0,255,255 64,191,255 102,153,255 128,128,255 146,109,255 159,96,255 170,85,255 179,77,255 185,70,255 191,64,255 196,59,255
9 0,255,255 85,170,255 128,128,255 153,102,255 170,85,255 182,73,255 191,64,255 198,57,255 204,51,255 209,46,255 213,43,255
10 0,255,255 128,128,255 170,85,255 191,64,255 204,51,255 213,43,255 219,36,255 223,32,255 227,28,255 230,26,255 232,23,255
11 255,255,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255
诸如针对五维混色网格颜色空间网格点阵列模型的构建，假设四元彩纤α、β、γ、δ、ε的重量分别为ω α＝10、ω β＝10、ω γ＝10、ω δ＝10、ω ε＝10，颜色值为α(0,255,255)、β(255，0,255)、γ(255,255,0)、δ(0,0,0)、ε(255,255,255)，分别将彩纤α的重量分成10等分，彩纤β的重量分成10等分，彩纤γ的重量分成4等分，彩纤δ的重量分成4等分，彩纤ε的重量分成4等分，并按等差数列进行配重，得到混合体ω ξ。将混合体ω ξ沿着点α、点β所在的面展开，可得125个11*11的面矩阵，在这里只例举前三个和最后三个，其他119个面矩阵可按照上述讨论出的面阵列矩阵计算得出，其对应的RGB值见颜色对照表，如下表3所示彩色纤维五维网格混色矩阵的颜色对照表。
表3
[ξ i,j,1,1，1] 1 2 3 4 5 6 7 8 9 10 11
1 0,255,255 23,232,255 43,213,255 59,196,255 73,182,255 85,170,255 96,159,255 105,150,255 113,142,255 121,134,255 128,128,255
2 0,255,255 26,230,255 46,209,255 64,191,255 78,177,255 91,164,255 102,153,255 112,143,255 120,135,255 128,128,255 134,121,255
3 0,255,255 28,227,255 51,204,255 70,185,255 85,170,255 98,157,255 109,146,255 119,136,255 128,128,255 135,120,255 142,113,255
4 0,255,255 32,223,255 57,198,255 77,179,255 93,162,255 106,149,255 118,137,255 128,128,255 136,119,255 143,112,255 150,105,255
5 0,255,255 36,219,255 64,191,255 85,170,255 102,153,255 116,139,255 128,128,255 137,118,255 146,109,255 153,102,255 159,96,255
6 0,255,255 43,213,255 73,182,255 96,159,255 113,142,255 128,128,255 139,116,255 149,106,255 157,98,255 164,91,255 170,85,255
7 0,255,255 51,204,255 85,170,255 109,146,255 128,128,255 142,113,255 153,102,255 162,93,255 170,85,255 177,78,255 182,73,255
8 0,255,255 64,191,255 102,153,255 128,128,255 146,109,255 159,96,255 170,85,255 179,77,255 185,70,255 191,64,255 196,59,255
9 0,255,255 85,170,255 128,128,255 153,102,255 170,85,255 182,73,255 191,64,255 198,57,255 204,51,255 209,46,255 213,43,255
10 0,255,255 128,128,255 170,85,255 191,64,255 204,51,255 213,43,255 219,36,255 223,32,255 227,28,255 230,26,255 232,23,255
11 255,255,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255 255,0,255
上面结合附图对本发明的实施方式作了详细说明，但是本发明并不限于上述实施方式，在本领域普通技术人员所具备的知识范围内，还可以在不脱离本发明宗旨的前提下做出各种变化。

Claims (5)

  1. 一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法，其特征在于：针对指定各基色纤维，以及维度数与基色纤维数相等的多维坐标系，以各基色纤维质量分别对应多维坐标系中的各根坐标轴，实现多维混色网格模型及网格点阵列颜色矩阵的构建，包括如下步骤：
    步骤A.根据各基色纤维别所对应的预设最大质量ω m，确定各基色纤维最大质量分别所对应其所设坐标轴的位置，然后进入步骤B；其中，m＝{1、…、M}，M表示基色纤维的数目，ω m表示第m根基色纤维别所对应的预设最大质量；
    步骤B.分别针对多维坐标系中原点与各根坐标轴上相应基色纤维最大质量位置之间的线段，执行n m等分，获得该线段上各点的质量
    Figure PCTCN2021082614-appb-100001
    i m表示第m根基色纤维所对应坐标轴线段上、由多维坐标系中原点至相应基色纤维最大质量位置方向各点的序号；n m表示针对第m根基色纤维所对应坐标轴上线段执行的等分数；然后进入步骤C；
    步骤C.构建多基色纤维分别所对应的混合比λ m(i 1,…,i m,…,i M)如下，然后进入步骤D；
    λ m(i 1,…,i m,…,i M)＝[ω m*(i m-1)/n m]/[ω 1*(i 1-1)/n 1+…+ω m*(i m-1)/n m+…+ω M*(i M-1)/n M]；
    步骤D.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的质量模型如下，然后进入步骤E；
    ω ξ(i 1,…,i m,…,i M)＝[ω 1*(i 1-1)/n 1+…+ω m*(i m-1)/n m+…+ω M*(i M-1)/n M]；
    其中，i m＝1、…、n m+1；
    步骤E.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的质量矩阵如下，然后进入步骤F；
    Figure PCTCN2021082614-appb-100002
    其中，i m＝1、…、n m+1；
    步骤F.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值模型如下：
    Figure PCTCN2021082614-appb-100003
    然后进入步骤G，其中，R 1、G 1、B 1表示第1根基色纤维所对应的RGB颜色值，R m、G m、B m表示第m根基色纤维所对应的RGB颜色值，R M、G M、B M表示第M根基色纤维所对应的RGB颜色值，
    Figure PCTCN2021082614-appb-100004
    表示多维坐标系中坐标(i 1,…,i m,…,i M)位置所对应各基色纤维混合纱线的颜色值，R ξ(i 1,…,i m,…,i M)、G ξ(i 1,…,i m,…,i M)、B ξ(i 1,…,i m,…,i M)表示多维坐标系中坐标(i 1,…,i m,…,i M)位置所对应各基色纤维混合纱线的RGB颜色值；
    步骤G.构建多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值矩阵如下：
    Figure PCTCN2021082614-appb-100005
    其中，i m＝1、…、n m+1。
  2. 根据权利要求1所述一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法，其特征在于：基于所述各基色纤维的最大质量与等分数就彼此相等，即各基色纤维对应的ω m彼此相等，各基色纤维对应的n m彼此相等，则步骤A至步骤G所获多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值模型如下：
    Figure PCTCN2021082614-appb-100006
  3. 根据权利要求1所述一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法，其特征在于：基于步骤A至步骤G所获多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值模型，以及各基色纤维对应的ω m彼此相等，各基色纤维对应的n m彼此相等，其中，基于(i 1,…,i m,…,i M)中任意K个参数分别为变量，其余参数分别为常数，针对
    Figure PCTCN2021082614-appb-100007
    构建(n m+1) M-K个(n m+1) K维的多维颜色阵列，其中，1≤K≤M。
  4. 一种针对权利要求1至3中任意一项所述一种彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法的应用，其特征在于：将所述多维混色空间网格模型所对应基于各基色纤维预设最大质量的立方体空间中任意网格点的颜色值，存储于数据库中，按如下方式，用于实现对目标颜色的分析；
    首选检测获得目标颜色所对应的RGB颜色检测数据，并在数据库中查找该RGB颜色检测数据所对应的网格点；然后在以该网格点为原点、周围预设半径范围，通过比对的方式，获得目标颜色所对应的网格点；最后由该网格点所对应的RGB颜色数据，构成目标颜色所对应的RGB颜色数据。
  5. 根据权利要求4所述一种针对彩色纤维多维混色空间网格模型及网格点阵列颜色矩阵构建方法的应用，其特征在于：采用检色仪针对目标颜色进行检测，获得目标颜色所对应的RGB颜色检测数据。
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