108 results about "Color analysis" patented technology

The invention relates to a dental color analyzing device comprising a housing, a computer device having a storage unit, and a display on which a reference object together with at least one tooth and / or a gingival area is represented, wherein at least one first image section that shows the reference object as well as at least one second image section that displays the tooth, a tooth region or a gingival area, may be detected with the aid of the computer device, characterized in that the reference object is mounted on a tooth and in particular is attached thereto and comprises a smaller size than the represented tooth, wherein the reference object is a dental color key comprising color samples that are arranged next to one another and that each represent a dental color, and in that the color of the second, in particular selectable image section, is comparable to the represented color samples with the aid of the computer device such that the color sample that matches the color of the second image section best, may be displayed on the display.

The invention relates to a color fiber multi-dimensional color mixing space grid model, a grid point array color matrix construction method and application, and the method comprises the steps of introducing a coordinate digital quantification process for each specified primary color fiber, enabling each primary color fiber to respectively correspond to each coordinate axis of a multi-dimensional coordinate system; taking the mass of the primary color fibers participating in mixing as coordinate axis data, obtaining a mixed yarn object of each primary color fiber through each grid point of a multi-dimensional coordinate system space, so that RGB color modeling of the mixed yarn object is realized in combination with the mixing ratio of each primary color fiber and the RGB color of each primary color fiber, namely, a multi-dimensional color mixing space grid model and a grid point array color matrix are formed, and therefore, the construction of a linear array model, a planar array modeland a body array model is further realized. Digital quantification is realized for an RGB color space under multi-primary-color fiber mixing, each group of models can be randomly called in practicalapplication to realize color visualization, and the color analysis and selection efficiency is effectively improved.

The invention relates to a waste plastic bottle sorting system comprising a detecting unit, a system control unit, a mechanical sorting unit and a conveying unit. The conveying unit sequentially feedswaste plastic bottles into the detecting unit and the mechanical sorting unit, and the system control unit is respectively connected with the detecting unit, the mechanical sorting unit and the conveying unit; the detecting unit comprises a visual detecting module, a material detecting module and a light source; and the visual detecting module performs information collection on color information,shape information and position information of the waste plastic bottles on the conveying unit based on a camera imaging principle. The waste plastic bottle sorting system has the advantage that visual color analysis and infrared material analysis are effectively combined, the information of the plastic bottles is accurately and quickly processed and transported to the mechanical sorting unit, andthe mechanical sorting unit can accurately conduct sorting operation on the plastic bottles on the conveying unit.

The invention belongs to the technical field of image processing, and relates to a colored textile fabric color difference degree detection method which is widely applied to the fields of artificial intelligence, color analysis, pattern recognition, intelligent detection and the like. According to the method, color space conversion is firstly carried out on an image, then global color features andlocal texture descriptors are extracted from HSV and Lab color spaces respectively, and finally corresponding features are fused to obtain mixed color space color representation features. According to the method, the defect that colors are described in a single color space is overcome, the color depicting capacity of the mixed color space is improved, the color difference degree is accurately detected, and the method has universality for different colored spun fabrics.

The invention relates to the technical field of data processing, in particular to a textile color detection method and system based on image recognition. The method can realize functions of integration service of information systems such as an artificial intelligence system in the production field, an artificial intelligence optimization operation system, artificial intelligence middleware, a function library and the like, and can also be used for development of application software such as computer vision software; the method comprises the following steps: acquiring images of a textile sample and a colorimetric card in different color spaces, preliminarily dividing color categories of the colorimetric card, and performing preliminary classification by combining a hue value of the textile sample and a hue value of a colorimetric card image; and obtaining the membership degree of the textile sample to each color block according to the saturation degree and the gray degree between the textile sample and each color block in the colorimetric card, wherein the color of the color block with the maximum membership degree is the color of the textile sample. According to the invention, the electronic equipment is used for image recognition, the accuracy and reliability of textile color analysis are improved, and the efficiency of color matching is improved.

The invention relates to the technical field of test paper color analysis, and particularly relates to a method for detecting sample substance concentration based on test paper image recognition. Themethod specifically comprises the steps of adding a sample, and collecting an image; carrying out normalization processing, and segmenting a detection item area; segmenting a blank test paper area; extracting color parameter values of the segmented images of the detection item area and the blank test paper area, and performing comparative analysis; inputting analysis results into a database, outputting a sample substance concentration value of each detection item. According to the method, the concentration of chemical substances in the sample can be output through image recognition and the technical principle of a reflection type photoelectric colorimetric method, and after the environmental parameter consistency and normalization processing at the shooting moment, the other environmentalfactors possibly influencing the output result are eliminated by a relative information comparison method, and the effectiveness of the output result is ensured without depending on the high consistency and stability of an optical component.

The invention discloses a smoke alarm device and method based on a smoke alarm. The signal of the device is connected to the smoke alarm and a user terminal. The smoke alarm is an indicator light, which sends out an indicator signal when a fire occurs. The device includes: A connected optical sensor and a signal generator, wherein the optical sensor includes a sequentially connected optical signal receiver, a color analysis module and a frequency discrimination circuit, and the signal generator includes: an information receiving circuit and an information library connected thereto. The method includes: monitoring whether the indicator light serving as a smoke alarm sends out an indicator signal; if yes, sending alarm information to the user terminal. Through the solution of the present invention, based on the monitoring of traditional smoke alarms (light alarms), the effect of synchronously reminding remote users in time is achieved.

A personal enhancing color selection system and method, in which a selected reflective material, preferably in the form of a fabric or woven drape, is placed near the face or skin surface of a subject person. The selected reflective material has a metallic sheen when reflecting an ambient light source. The selected reflective fabric material is either a silver-hued material, a copper-hued material, or a gold-hued material. The incident light from the ambient light source imparts a reflected light onto the skin surface, with the copper material imparting a copper toned reflected light, the silver-hued material imparting silver toned reflected light, and the gold material imparting a gold toned reflected light. A visual determination of an aesthetically appealing augmentation to the skin surface is made, to recommend haircoloring, clothing colors and makeup selections that will likewise produce a positively enhanced appearance of the subject person of the color analysis.

The invention discloses an optimal grain direct selection method for a rice color selector, and relates to the technical field of rice color selection, which comprises the following steps of: traversing an image to be identified line by line and pixel by pixel, performing weighted gray processing on effective material pixel points in the image, if a gray value is smaller than a black threshold value, judging the pixel point as a black pixel point, otherwise, carrying out color analysis on the pixel point, and if the pixel point is within a preset yellowing material RGB range, judging that thepixel point is a yellow pixel point; if the sum of the number of the black pixel points and the number of the yellow pixel points on one rice grain is smaller than an allowable threshold value, judging that the rice grains are high-quality rice grains. According to the method, the high-quality rice grains are directly screened out by accurately identifying the blackened and yellowed rice grains and / or the blackened and yellowed parts in the rice grains, so that the working efficiency and accuracy of high-quality rice grain sorting are greatly improved.

The invention relates to a wastewater decolorization reaction automatic tracking operation method, which comprises the following steps of: obtaining the color and property of wastewater before the wastewater treatment decoloration reaction, further searching operation records in an automatic operation database of the wastewater decoloration reaction by using an AI intelligent color recognition host, obtaining a treatment process formula loaded by a similar operation process, further automatically operating a wastewater decolorization reaction program to obtain reacted wastewater color information and operation data information, intelligently comparing color changes before and after reaction, analyzing a decolorization reaction effect, and further adjusting an operation process or directlystoring the operation process into a wastewater decolorization reaction operation database, and the method is used as a process formula for automatically operating decolorization reaction of wastewater with the same color and property in future. By analyzing the change information of the effective decoloration reaction color, the wastewater treatment decoloration reaction is more accurate, historical data and artificial intelligence color analysis are used to master and correct the operation of the automatic decoloration reaction, and the automatic tracking operation target of the wastewater treatment decoloration reaction is realized.

A full-width array spectrophotometer for full-width scanning color analysis of a color inspection object having a plurality of different colors of a multiple repeating pattern of at least three or four different colors laterally covering a path of printing paper and illuminated in succession One or two generally linear elongated illumination arrays of closely spaced multiple LED illumination sources emitting to sequentially illuminate transverse illumination bands on printed paper moving along said paper path; also comprising corresponding elongated low cost A photoimaging strip comprising a parallel and corresponding plurality of closely spaced elongated arrays of differently color-sensitive (three or four rows of color-filtered) photodetectors arranged to detect and analyze light from Light reflected by laterally successively illuminated strips.

A chemical indicator solution, an apparatus, and a method for determining concentration of a chemical analyte is provided. In particular, the apparatus provides a simplified and low cost way to determine that a fluid sample contains a minimum recommended concentration of a chemical. Rather than using complex and expensive components or error-prone manual methods to prepare the solution and measure chemical concentrations, the apparatus may allow for the automatic measuring and mixing of the chemical components of the resulting solution through the unique geometry and layout of the apparatus. The resulting solution may contain a chemical indicator which allows for the detection of the concentration of the chemical analyte within the resulting solution using techniques such as color analysis.

The invention discloses an intelligent lighting control system based on big data. Existing Internet of Things lighting equipment is used, like an RGB LED intelligent lamp, and is accessed to the Internet of Things in coordination with a wireless data transmission mode to be linked with other Internet of Things intelligent devices like an intelligent display terminal, a sound source positioning module, an image acquisition module, a color analysis module and a light control module as big data acquisition devices. And display parameters of a display area on the outermost circle of the intelligent display terminal, position information of the intelligent display terminal in a room, classification information of application programs and the like are collected to form big data, and processing and analysis are carried out on the big data to obtain lighting parameters of each LED intelligent lamp. Better immersion experience is achieved during entertainment, manual setting is not needed, andthe display position and the color effect of the lamp can be adjusted in real time. The equipment has no need to be close to a wall, and the use position is more flexible.

The invention belongs to the field of deep learning, relates to a fabric image super-resolution reconstruction method, and is widely applied to the fields of color analysis, texture structure research, pattern recognition and the like. The method comprises the following steps: grouping and down-sampling acquired images, then establishing an SRGAN network by using basic structures of a GAN and a Resnet50 network, and then training the network in three steps by using a preprocessed fabric image as input and testing by using the test data set after the training is finished and evaluating the network performance by using the PSNR. According to the method, the resolution of the fabric image can be greatly improved, detail parts are richer and the method has ideal robustness and wide applicability.

The invention relates to a face spoofing detection method based on color analysis, and belongs to the field of digital image processing and pattern recognition. The method comprises the following steps: an image preprocessing stage: cutting a face region into image blocks with the size of 128 * 128 from a video; a feature extraction stage: extracting features of the image through a local binary pattern and a color distance; and a classification stage: fusing the local binary pattern and the color distance feature vector, and then performing classification by using a support vector machine to obtain a result. According to the method, color information can be added on the basis of texture features, and the method is applied to face spoofing detection and can better help a system to learn color information between a real face and a counterfeit face. And meanwhile, compared with other methods for introducing color information, the method provided by the invention has the advantages of smaller calculation amount and higher calculation speed.

The invention discloses a color image edge extraction method, and belongs to the technical field of image processing. The invention discloses a color image edge extraction method, and the method comprises the following steps: S1, noise reduction: performing noise reduction on an image by adopting a noise reduction method based on a threshold value; S2, image color structure analysis: carrying out color analysis on the image structure through an RGB model and an HSI model; S3, designing of an algorithm to extract a color edge: designing an algorithm comparison threshold, determining color edge points, and forming the color edge by a plurality of edge points. According to the method, the accuracy of color image edge extraction is improved, and a good basis is provided for subsequent image processing.

The invention discloses an intelligent plastic sheet color sorting method based on image processing, and relates to the technical field of color sorting algorithms. The method comprises: performing color analysis on an obtained plastic sheet image line by line and pixel by pixel, and if the pixel coverage rate of a target color belonging to the plastic sheet image exceeds a threshold value, judging that the plastic sheet is a target plastic sheet. According to the invention, microscopic pixel point identification is carried out on the plastic sheet, and whether the plastic sheet is a target plastic sheet is judged by counting the color space to which each pixel point belongs, so that accurate color sorting of the plastic sheet is realized.

The invention relates to the technical field of test paper color analysis, in particular to a method for detecting sample substance concentration based on pushing direction identification of a urine drying test strip, which specifically comprises the following steps of: firstly, obtaining color block RGB (Red, Green and Blue) data by camera timing integration, and inputting the color block RGB data into a color calibration matrix to obtain a standard color and a calibration value; the method comprises the following steps: firstly, carrying out calibration on a to-be-detected item, then circularly searching whether the to-be-detected item still exists or not, if so, moving to a next detection color block, carrying out color integration with the same time length to obtain RGB data, then combining with a calibration value to obtain calibrated RGB data, entering an analysis module, firstly converting the RGB data into LAB spatial data, carrying out same-color system judgment, if in the same color system, calculating a Lab spatial Euclidean distance, and if in the same color system, calculating a Lab spatial Euclidean distance; if not, a color difference comparison algorithm is adopted for optimization, color difference comparison is carried out, and the color with the minimum color difference is selected; and then searching a corresponding sample concentration value as a detection result, and finally returning to the circulation until all items are detected and exiting the circulation.

The invention relates to a construction method and application of a color fiber three-dimensional color mixing space grid model and a grid point array color matrix, aiming at the expression problem ofa specified three-primary-color fiber digital color mixing effect, taking the mass omega alpha, omega beta and omega gamma of three-primary-color fibers as carriers, and respectively corresponding the carriers to each coordinate axis of a three-dimensional coordinate system, through meshing division of omega alpha, omega beta and omega gamma axes, one-dimensional straight line, two-dimensional plane and three-dimensional mesh division in a three-primary-color color mixing space mesh model is realized, so that a mesh model of a color fiber three-dimensional color mixing space is constructed; and digital expression of corresponding chromatograms is realized by constructing grid point array matrixes and array color matrixes of points, lines, surfaces and bodies in the three-dimensional colormixing space. In practical application, the model and the algorithm can automatically set gridding precision, and each group of model algorithms is called to realize visualization of gridding chromatography, so that the color analysis and selection efficiency is effectively improved.

The invention discloses a financial product recommendation method and system based on artificial intelligence, and the method comprises the steps: inputting the total amount of assets of a first user, the number information of economic sources, and the type information of the economic sources into an economic source grade evaluation model, and obtaining the economic source grade information of the first user; according to the bearable risk level of the first user and the saving ratio, obtaining a financial idea color analysis result of the first user according to the predetermined color mapping area; and adjusting the first financial product list according to the financial idea color analysis result of the first user to obtain a second financial product list, and pushing the second financial product list to a client of the first user. The technical problems that in the prior art, most financial products are recommended manually, efficiency is low, and accurate recommendation cannot be conducted according to personal requirements are solved.

The invention discloses an instrument color state identification method for an unmanned inspection system of a transformer substation. The method comprises the following steps: step 1, shooting an instrument display panel image through a camera system; step 2, selecting, intercepting and separating a to-be-identified area through an auxiliary tool; 3, performing color classification judgment on the to-be-identified area by adopting a color analysis algorithm; 4, matching the color classification judgment with the preset signal color of the instrument; and 5, transmitting a corresponding inspection signal to the inspection management and control personnel according to the matching result. The method can achieve the automatic recognition of the color of the indication lamp of the instrumentpanel.

The invention provides a color matching method and device for a patch model, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: obtaining the color distribution information of the to-be-matched patch model according to the corresponding relation of file contents contained in the to-be-matched patch model, determining color matching degree information between the to-be-matched patch model and other patch models to select a target patch model matched with the to-be-matched patch model from the other patch models, and determining a color matched with the to-be-matched patch model according to the target patch model to recommend an article model. According to the method and device, the electronic equipment and the storage medium, the problem of color matching degree between color extraction and determination of the surface piece model is solved, so that the color matching requirement of the object model and the color analysis requirement of the surface piece model are met, color matching of different objects is accurate and rapid, and the quality of AI home decoration design can be ensured.

The invention relates to a method for constructing a high-dimensional discrete chromatography and a visualization method of a multi-component mixed-color fiber system. For multi-primary color fibers, a coordinate digital quantification process is introduced, fiber mass is equally divided corresponding to coordinate axes, and a mixed yarn object in a multi-dimensional coordinate system space is obtained according to the mass of mixed fibers corresponding to points on the coordinate axes. Therefore, RGB color modeling of the mixed yarn object is realized by combining the mixing ratio of each primary color fiber and the RGB color of each primary color fiber; in other words, the color matrix of the color mixing system and the visual color mixing chromatography matrix of the color mixing system are formed, and visualization is achieved for the high-dimensional discrete chromatography constructed for the multi-element color mixing fiber system. According to the method, each group of models can be randomly called in practical application to realize color visualization, so that the color analysis and selection efficiency is effectively improved.

The invention discloses an automatic testing system and method for non-standard display equipment. The system comprises a host, a power supply module, a video signal source module and a color analyzer, the power supply module is used for supplying power to the tested display equipment; the video signal source module is constructed on the basis of FPGA technology and used for providing non-standard video signals in a TTL format for a tested display device. The color analyzer is used for carrying out color information analysis on the tested display equipment; the host is used for sending a power supply instruction, an image output instruction and a color analysis instruction; and the host is also used for carrying out communication protocol verification according to the communication information of the communication interface and the tested display equipment. A video signal source module constructed based on the FPGA technology is adopted, non-standard video signals can be output, a color analyzer automatically analyzes color information, and color analysis and measurement efficiency is effectively improved. According to the scheme, testing of display parameters, video signal integrity and a communication protocol can be automatically completed, manual participation is reduced, the testing efficiency is improved, and the consistency of products is guaranteed.

The invention relates to a color fiber four-dimensional color mixing space grid model and construction method and application of the grid point array color matrix, aiming at the expression problem of a specified four-primary-color fiber digital color mixing effect, taking the mass omega alpha, omega beta, omega gamma and omega delta of four-primary-color fibers as carriers, and respectively corresponding the carriers to each coordinate axis of a four-dimensional coordinate system. Through meshing division of omega alpha, omega beta, omega gamma and omega delta axes, meshing division of a one-dimensional straight line, a two-dimensional plane, a three-dimensional space and a four-dimensional space in the four-primary-color color mixing space mesh model is realized, so that the mesh model of the color fiber four-dimensional color mixing space is constructed. Digital expression of corresponding chromatograms is realized by constructing grid point array matrixes and array color matrixes of all points, lines, surfaces, bodies and four-dimensional spaces in the four-dimensional color mixing space. In practical application, the model and the algorithm can automatically set gridding precision, each group of model algorithms is called to realize visualization of gridding chromatography, and therefore the color analysis and selection efficiency is effectively improved.