661 results about "Color recognition" patented technology

The invention belongs to the field of environment monitoring and computer vision, and particularly relates to a water body color recognition regression method and system based on space-time causality and manifold learning, and the method mainly comprises the steps: carrying out the detection of a current target water body video sequence, extracting a water body region, carrying out the high-dimensional feature dimension reduction of the water body region, and obtaining a water body color recognition result; and performing feature extraction on the water body region through a space-time causal feature learning model, fusing the flow shape learning features and the space-time causal features to obtain fused features, and outputting a finally predicted water body color value. According to the method, end-to-end assembly line design of preprocessing-segmentation-feature modeling-regression is adopted, manual intervention is not needed from video input to color prediction, and through cascade cooperation of five core modules (video preprocessing, water body segmentation, manifold learning, time sequence causal modeling and color recognition), the real-time performance of the system is improved. Full-link automation from environmental interference suppression, feature extraction to result output is realized, information loss of intermediate links is avoided, and recognition efficiency and robustness are improved.

The invention relates to the technical field of textile detection, and provides a fabric sticky hair identification method and identification system based on fluorescence enhancement and machine vision, and the fabric sticky hair identification method comprises the following steps: carrying out fluorescent dyeing on a fleece when the fleece is dyed; rubbing the fuzzing cloth with a to-be-detected fabric so as to enable the to-be-detected fabric to be fuzzed; placing the to-be-detected fabric in a preset environment so as to enable the sticky hair on the to-be-detected fabric to emit fluorescence; acquiring a surface image of the to-be-detected fabric after hair sticking and fluorescent color development; analyzing the area proportion of a fluorescent region in the surface image based on image color identification; and according to the area proportion of the fluorescent region, determining the hair sticking grade of the fabric to be detected. According to the invention, the problem that the precision and reliability of sticky hair detection are seriously influenced by material and color differences of a machine vision detection system in the prior art can be solved.

The invention belongs to the technical field of optical lenses. The invention relates to a butterfly pupil escape compound eye bionic high-color-gamut nylon sunglass lens which comprises a lens body and a coating. Wherein the lenses are made of nylon resin; the coating is prepared from the following raw materials in parts by weight: 25 to 40 parts of tetraethoxysilane; 10 to 20 parts of phenyl trimethoxy silane; 4.0 to 8.0 parts of dimethyl dimethoxy silane; 2.0 to 4.0 parts of an MOF color enhancing agent; 20 to 30 parts of isopropanol; 11 to 22 parts of deionized water; and 1.0-3.0 parts of glacial acetic acid. A coating is prepared from a self-made MOF color enhancing agent through molecular design through formula optimization design, and the nylon resin lens is coated with the coating, so that the butterfly pupil escape compound eye bionic high-color-gamut nylon sunglasses lens is obtained. The butterfly pupil escape compound eye bionic high-color-gamut nylon sunglass lens effectively solves the problem that the color identification degree is low after the butterfly pupil escape compound eye bionic high-color-gamut nylon sunglass lens is blocked by 45-90% of light rays at present.

The embodiment of the invention provides a color recognition method and system for pH test paper detection, and belongs to the technical field of image processing. Acquiring standard color card data; defining an identification area; according to the identification area, obtaining position information of a color block of the pH test paper; and obtaining color information of the color block of the pH test paper according to the position information of the color block of the pH test paper and the standard color card data. The method can improve the recognition precision, is more suitable for improving the color recognition precision based on a single-chip microcomputer, and is high in cost performance.

The invention relates to an intelligent environment color recognition method, which realizes accurate control of a color recognition technology under the working condition of a sea-land dual-purpose sound and temperature hidden transfer device, and comprises the following steps that: an image acquisition module acquires various kinds of environment image data; the preprocessing module optimizes the image quality and the data format; the color feature extraction module extracts multi-dimensional features by using a deep learning algorithm; the deep learning model module learns a mapping relation through mass data training; the color recognition module feeds back and accurately recognizes colors based on the training model and the confidence coefficient; and the result output module displays the result in a plurality of visual modes. The environment color recognition method improves the color recognition accuracy and adapts to complex environment illumination and color combination; the method has good adaptability and is suitable for various scenes; reliable data processing is guaranteed, real-time performance, stability and personalized control are achieved, and user experience and working efficiency are improved.

The invention discloses an indicator light multi-state cascade identification method based on a deep learning shared network, and belongs to the field of intelligent inspection of power equipment. According to the method, low-order textures and spatial features of an image are extracted through a unified convolutional neural network, and a shared feature map is formed; a channel separation mechanism is adopted, the shared feature map is distributed to color recognition and state detection parallel branches according to dimension weights, the form discrimination branch on the uppermost layer analyzes geometric contour features through a full-connection layer, and circular / strip-shaped classification is achieved; the color identification branch adopts a dual-channel convolution kernel to respectively strengthen red / green spectral response, and color judgment is completed through feature map comparison; state detection branches fuse space pooling and brightness statistical analysis, and a decision boundary of an on-off state is established. According to the method, parameter redundancy can be reduced, the identification precision of each sub-task is improved, and the requirement of the inspection equipment for real-time judgment of a multi-dimensional state is met.

The invention relates to a computer vision technology, and discloses a laying hen health condition monitoring method and system based on a cockscomb form, and the method comprises the steps: collecting laying hen cockscomb images according to a preset time interval, and forming an image sequence; and carrying out gravity center identification on each image in the sequence, obtaining gravity center sequence data and analyzing gravity center offset. If the center-of-gravity offset exceeds a preset threshold value, color identification is directly carried out on the current image to obtain color data, and if the center-of-gravity offset does not exceed the preset threshold value, the form variation of the cockscomb edge area in the image sequence is analyzed. When the form variation is greater than a preset threshold value, judging that the laying hen is healthy; and if not, returning to execute the color identification step. And finally, performing disease judgment according to the color data to obtain a judgment result. The laying hen health condition monitoring efficiency can be improved.

The invention provides a target tracking control method and device based on image recognition and a camera, and relates to the technical field of automatic control. The method comprises the steps of performing color recognition on a target image through an adaptive color recognition algorithm, recognizing a color region and calculating a color center coordinate; identifying the target image through a pre-trained YOLOv2 target detection model, and calculating object center coordinates according to the identified object area; and calculating a tracking center coordinate according to the color center coordinate and the object center coordinate, converting the tracking center coordinate into a motion control signal to drive the visual sensor to rotate, calculating an actual rotation angle of the visual sensor through a PID control algorithm, and correcting the rotated visual sensor according to a calculation result to realize target tracking. The central position of the target is found through color recognition and object recognition, and the visual sensor is driven to rotate to track the target, so that the target is located at the central position of the image in real time.

The invention discloses a multi-channel integrated marketing contact content management system and method, and relates to the technical field of marketing contact content auditing, and the method comprises the steps: creating a plurality of marketing contacts in a unified management platform, and configuring a delivery channel; establishing a design specification rule base; receiving a marketing content picture uploaded by the user and associating the target channel with the contact; calling a rule base on the basis of a contact type, starting an AI auditing engine to carry out automatic compliance inspection on the picture, including preprocessing, layout identification, character extraction and character number statistics, font and character size identification, color identification and functional element detection, and comparing an identification result with a rule to generate an auditing result; and approving the delivery of compliant content and tracking the effect, and optimizing an AI engine and a rule base based on data. According to the method, AI intelligent auditing is embedded into the marketing content publishing process, multi-channel integrated management and intelligent auditing of the marketing content are achieved, the auditing efficiency and accuracy are remarkably improved, it is guaranteed that the content is standard and unified, and the labor cost is reduced.

The invention discloses an electric vehicle rear-end collision accident prediction method and system based on large model knowledge and trajectory data. According to the method, two vehicle types of an electric vehicle and a fuel vehicle are identified based on license plate colors, the vehicle types and vehicle tracks are bound, and the following process is divided into three states according to the combination of the front and rear vehicle types. On the basis, multi-dimensional features extracted from historical tracks are input into a large language model, expert-level rule knowledge used for distinguishing accidents and non-accidents is extracted through structured cues, and a final feature matrix is constructed according to the knowledge. And finally, based on the final feature matrix, performing differentiation processing on the three car-following states, training and calibrating a dichotomy model, and realizing real-time estimation of the rear-end collision probability at a specific moment in the future. According to the invention, by fusing the reasoning ability of the large model and the real trajectory data, the accuracy and interpretability of rear-end collision risk identification under the electric vehicle participation scene can be significantly improved, and the method has engineering deployment value.

The invention discloses a soil color exploration and identification system and method, belongs to the technical field of soil color identification, can effectively reduce the influence of ambient light on soil color discrimination through a standardized color correction board and software image processing, and performs hierarchical division on a soil color identification image along a vertical plane, thereby improving the accuracy of soil color identification. Pixel point color information of a plurality of independent soil layers is obtained, so that the color distribution uniformity of a single layer is judged, then the color distribution condition of the whole image is comprehensively analyzed to divide soil types, and different color recognition modes are selected according to the judged soil types to be compared with a colorimetric card digital image. Compared with a mode of directly extracting color information of an overall image and comparing a colorimetric card, hierarchical division is adopted, single-to-overall soil type judgment is carried out, and a proper recognition mode is selected according to a judgment result, so that the color recognition accuracy is effectively improved.

The invention provides a vision-based paper anomaly detection method and device, and the method comprises the steps: configuring a template drawing for a detection region, determining a detected effective region mask according to the template drawing, and setting a counting standard-reaching parameter; collecting a preset number of initial environment images in the detection area for initial judgment when detection is started; after the initial judgment is completed, collecting a real-time environment image according to a preset time interval, determining an effective area and an invalid area in the real-time environment image according to the effective area mask, performing color recognition on the effective area in the real-time environment image, and performing frequency domain calculation on the invalid area; according to an effective area color identification result and an invalid area frequency domain calculation result of the real-time environment image and the counting up-to-standard parameter, whether paper breaking and shielding occur currently is judged; the method can improve the reliability of broken paper detection.

The technical problem to be solved by the invention is to provide the micro-plastic detection and degradation device which can realize detection and decomposition of micro-plastic and effectively reduce micro-plastic pollution sources. The device comprises a base, a power supply assembly, a detection and degradation assembly and a control assembly are arranged on the base, and the detection and degradation assembly and the control assembly are electrically connected with the power supply assembly; the detection and degradation assembly comprises a bacterial liquid container, a reaction container, a micro-plastic liquid container and a detection container, the reaction container is provided with a temperature sensor and a PH value sensor, the detection container is provided with a color recognition sensor, and the micro-plastic is subjected to color reaction after being combined with the colloidal gold; the RGB value of the color appearing after the micro-plastic and the colloidal gold are combined is measured through the color recognition sensor and transmitted to the control assembly, the concentration of the micro-plastic liquid is obtained through calculation, the micro-plastic is degraded through biological reaction by mixing the bacterial liquid and the micro-plastic liquid, and the purpose of degrading the micro-plastic is achieved.

The utility model relates to the technical field of toys, in particular to an interactive educational toy for children, which comprises a support and a plurality of pressure sensors fixedly connected to the top of the support at equal intervals. And the number of the storage assemblies is multiple, the number of the storage assemblies is equal to that of the pressure sensors, each storage assembly comprises multiple fixing rods and multiple snowflake building blocks, and baffle rings are fixedly connected between the upper end faces of the multiple fixing rods. According to the snowflake building block toy, after a child finishes an educational toy snowflake building block game, parents can guide the child to store and arrange the snowflake building blocks by themselves, the loudspeaker can send out audio frequency to guide and encourage the child to store the snowflake building blocks, and the child can improve color recognition and manual operation ability through interactive storage. And a good habit of self-storage of personal articles can be developed, and a good interactive education effect is achieved.

The invention discloses a high-precision color identification method for a complex light source environment, and relates to the technical field of color identification. The method specifically comprises the following steps: 1) constructing a hardware system; 2) carrying out image preprocessing; 3) extracting image features by using an improved YOLO algorithm, performing multi-scale feature fusion by using a feature pyramid network, and correcting color distortion caused by a light source, equipment or a material in combination with a color restoration algorithm to ensure real restoration of the color; 4) designing a color evaluation algorithm, outputting color parameters such as a Lab value and a delta E value, accurately evaluating the color, and performing color difference comparison; 5) establishing a standard database, supporting the learning and optimization of historical data, and improving the identification accuracy of a new sample; 6) an automatic operation process; according to the method, advanced hardware configuration, deep learning, color restoration and automatic control technologies are combined, high-precision color identification in a complex light source environment is facilitated, and the method has a wide application prospect.

The utility model relates to the technical field of color sorters, and discloses a color sorter which comprises an inclined plate, a hopper is fixedly connected to one side of the upper end of the inclined plate, a discharging roller is rotatably connected to the bottom end of the interior of the hopper, a plurality of material distributing grooves are formed in the outer wall of the discharging roller in an annular array mode, and a discharging opening is formed in the bottom end of the hopper. And a shading plate is fixedly connected to the upper end of the inclined plate, a plurality of visual cameras arranged in a linear array are arranged at the upper end of the shading plate in a penetrating mode, and light supplementing lamps are fixedly connected to the two sides of the interior of the shading plate. According to the color sorter, through the design of the discharging roller and the material distributing groove in the hopper, materials can be evenly and continuously separated and conveyed to the inclined plate, high-speed and accurate color recognition is conducted in cooperation with the visual camera, the sorting efficiency is improved, meanwhile, the light supplementing lamp provides even and sufficient light, it is ensured that the visual camera can capture clear material images, and the color sorting efficiency is improved. Therefore, the screening precision is improved.

Battery life cycle management is facilited with distinct visual cues of colors and color-coded combinations. The color-codes enable battery types and characteristics over the course of the life of the battery to be determined. The color-codes are based on a color system that indicates a performance rating of the batteries. A system for managing the color-coded batteries selects color-coded batteries for use based upon color, maintaining color based functionality, and color-coded battery indication for destruction of the battery at the end of its life cycle.

The embodiment of the invention discloses a classification detection method and system for detecting two-dimensional code label defects based on lightweight convolution. The efficiency and accuracy of two-dimensional code label printing defect detection can be improved. The method comprises the following steps: S1, acquiring a two-dimensional code label in a label printing area by using a high-resolution camera to obtain a camera rough image; s2, in combination with HSV color recognition and threshold segmentation, taking the two-dimensional code label as an ROI region to perform feature extraction on the rough image of the camera to obtain a fine contour image of the two-dimensional code label; s3, a lightweight convolution module LRB is used for extracting defect features of the two-dimensional code label in the fine contour image, the lightweight convolution module LRB is constructed based on a ghost module GM and a lightweight residual block, and the lightweight residual block is designed to be of an inverted residual block structure composed of linear bottleneck structures; using a ghost module GM to replace the inverted residual structure and a depth separable convolutional layer in the two-dimensional convolutional layer; and S4, using a Softmax classification layer to predict the defect features of the two-dimensional code labels and outputting a defect classification result.

In order to solve the problem of intelligent screening of colors of waste glass, the invention designs an intelligent screening device for waste glass, and the device is sequentially provided with an electromagnetic vibration feeder, a chute, a light source, an image acquisition and recognition device, a pneumatic injection device and a glass classification storage device from an input end to an output end. According to the method, the colors of the waste glass particles are collected, the colors of the waste glass particles are recognized through an image recognition and processing algorithm, and then the waste glass is classified and screened by controlling a pneumatic injection device according to the recognition result. The intelligent waste glass color screening system which is convenient, rapid and high in screening precision is provided for waste glass color screening.

The invention discloses a game anti-plug-in Ai algorithm ESP protection mechanism, which is used for protecting game speed, blood volume encryption, equipment encryption, simulated mouse encryption, mouse track analysis, game character blood strip encryption and infinite blood strip technology, and enabling a client to support speed control, vulnerability repair, infinite blood encryption and infinite equipment encryption expansion. According to the method, the game client can be effectively prevented from being modified and invaded by the plug-in, and the security and integrity of the game data are protected. The AI behavior detection technology can recognize abnormal behaviors in real time, the attack difficulty of the plug-in is further improved through the functions of a speed sealing system, an anti-simulation keyboard and mouse and the like, the use scenes of the plug-in are reduced through the measures of multi-open control, virtual machine detection and the like, and the graph color type on-hook behaviors are effectively attacked through the graph color protection function. The whole protection mechanism combines data encryption, an AI algorithm and multi-dimensional protection control, a set of complete game anti-plug-in solution is formed, and powerful guarantee is provided for fairness and stability of games.

The utility model relates to a spray cooling device based on color identification, which comprises a cover body, a heat source, a cooling circulation system, a temperature sensor, a color identification sensor and a control unit, the cover body covers the outer side of the middle upper part of the heat source, the cooling circulation system comprises a cooling liquid cylinder filled with cooling liquid, and a water outlet pipe of the cooling liquid cylinder is connected with a water pump; an outlet of the water pump is connected with a water spraying pipe and an overflow pipe in two ways, an electromagnetic valve is arranged on the water spraying pipe, a nozzle is arranged at the front end of the water spraying pipe and extends into the cover body to directly face the heat source, and an overflow valve is arranged on the overflow pipe which is connected to a water inlet pipe of the cooling liquid cylinder; a water outlet is formed in the bottom of the cover body and connected to a water inlet pipe of the cooling liquid cylinder through a water drainage pipe. The temperature sensor is arranged in the heat source, the color recognition sensor is arranged above the heat source in the cover body, and the control unit is electrically connected with the temperature sensor, the color recognition sensor and the electromagnetic valve. The device is beneficial to timely and reliable spray cooling, and the use of cooling liquid is reduced.

The embodiment of the invention provides a method and system for color recognition control of pH test paper, and belongs to the technical field of image processing. According to the position information of the sampling rod, the coordinate information of the test paper is obtained; sampling dropping liquid, and acquiring dropping liquid information according to the coordinate information of the test paper and the position information of the sampling rod; adjusting the color proportion of the reference color block; obtaining color information according to the color proportion and the liquid dropping information; and calculating the color information to complete identification control. According to the invention, the accuracy and robustness of a color recognition system can be improved.

The invention discloses an eye disease analysis method based on an eye image, and the method comprises the steps: carrying out the image segmentation of a sclera region through employing a convolutional neural network architecture u-net network model of image segmentation, carrying out the recognition of a hyperemia part of the sclera region, and calculating the proportion of the hyperemia part through employing FrangiFilter blood vessel recognition in combination with the color recognition of an LAB color space; by combining the image algorithm with a traditional image processing and deep learning model, the segmentation precision of the sclera region, the identification precision of sclera congestion, the robustness, the high accuracy and the rating accuracy are improved under the condition that the operation speed is not reduced.

The invention relates to the technical field of wire core wires, and discloses a wire core wire color identification and tiling method which comprises the following steps: 1) identifying an initial position of a set core wire through a camera, and rotating the set core wire to a set position; 2) arranging the plurality of core wires side by side in sequence; 3) pulling the plurality of core wires into a straight line shape; the initial position of a set core wire is recognized through a camera, the set core wire is rotated to the set position through rotation, core wire color recognition operation is achieved, then a plurality of core wires which are spatially staggered abut against the same plane through a flattening structure so that the core wires can be sequentially arranged side by side, and then the core wires are movably clamped through a straightening structure. And the core wires are pulled linearly relative to the plurality of core wires, so that the plurality of core wires are pulled to be linear, the plurality of core wires are tiled, the operation efficiency is high, and the cost is greatly saved.

The invention relates to a toy waste color classifying and sorting method and system. The method comprises the following steps that a CCD camera module is adopted to capture images of toy waste passing through a conveying belt in real time; the image is preprocessed; performing color feature extraction on the preprocessed image through an image processing unit, comparing color information of the toy waste with a predefined color model by adopting a color recognition algorithm, and generating a classification result; according to a color identification result, generating a corresponding classification signal; the classification signal is received, and a mechanical arm module is controlled to grab the toy waste according to the target color category; according to the toy waste color classifying and sorting method and system, automation and intellectualization are achieved in toy waste color classification, the classification efficiency is improved, the classification accuracy is guaranteed, and therefore effective technical support is provided for environmental protection and resource recycling.

The invention discloses an intelligent regional refrigeration adjusting system and method based on multi-mode sensing, relates to the technical field of refrigerated cabinets, and aims to solve the problem that a traditional refrigeration device only conducts passive adjustment through pressure and temperature and cannot sense material decay in the early stage. The system comprises a pressure / temperature acquisition module, a state sensing module (a color recognition unit and a smell recognition unit), a grading decision module and a cold supply adjusting module, and material states are divided into L0-L3 four levels; according to the method, multi-modal data are synchronously obtained through a depolarization method, color / smell change indexes are obtained after processing, state grades are judged, customized cold supply instructions (such as L1 cooling and wind speed increasing and L3 limit refrigeration and isolation) and early warning instructions are generated in combination with pressure and temperature, and the instructions are independent in different areas.

The invention discloses an image resolution monofilament detection system and method, and relates to the technical field of monofilament detection. According to the image resolution monofilament detection system and method, a high-resolution camera is used for collecting a marked area image caused by an identification accessory on a chemical fiber godet wheel in real time, an image processing module is used for carrying out noise removal and color space conversion on the image, and a Canny edge detection algorithm is used for extracting the edge contour of the image. And the color identification module analyzes the color change of the marked area through a contour tracking algorithm, calculates to obtain a broken wire index, and judges whether the marked area is a broken wire area according to a preset threshold value. The broken wire judgment module judges whether the wire guide wheel rotates or not according to the color recognition result so as to judge whether the wire is broken or not, and early warning information is sent out when the wire is broken. The system can accurately monitor the yarn breakage problem in the chemical fiber production process, and has efficient and real-time yarn breakage detection capability.

The invention discloses a line sequence automatic detection algorithm based on machine vision and an implementation method thereof, and belongs to the technical field of machine vision and image processing. Aiming at the problems of low efficiency and poor accuracy of traditional manual detection of a multi-core cable, the invention provides the following technical scheme: preprocessing a collected cable image, and enhancing the image by adopting adaptive histogram equalization of an LAB color space; determining a scanning band at the center of the image and converting the scanning band to an HSV color space; the comprehensive value of the HSV color gradient is calculated, the peak value is detected by adopting an adaptive threshold value, and the boundary of each wire core is accurately positioned; establishing an HSV (hue, saturation and value) feature library containing 10 standard colors, and realizing color matching through weighted distance measurement; and an automatic detection mode and a manual assistance mode are provided. According to the method, the detection accuracy reaches 95% or above, the processing time of a single image is shorter than 1 second, the technical problems of automatic color recognition and sorting detection of the multi-core cable are effectively solved, and the method can be widely applied to cable production quality control.

The utility model discloses an ultraviolet analyzer for pesticide residue detection, and relates to the technical field of ultraviolet analyzers, the ultraviolet analyzer comprises a detection mechanism used for realizing real-time detection and recording of colors, the detection mechanism comprises a box body assembly, the box body assembly comprises a box body, a camera is fixedly installed at the top of an inner cavity of the box body, and the camera is connected with the box body assembly; an ultraviolet lamp is fixedly mounted at the top of an inner cavity of the box body; the sampling assembly is arranged in the box body assembly and is used for conveniently putting in and taking out a sample; the adjusting supporting leg assembly is arranged at the bottom of the box body assembly and used for adjusting the flatness of a box body, a camera is fixedly installed on the left side of the top of the box body, a lens of the camera is aligned to the upper portion of a drawing plate, a sample emits fluorescence under irradiation of an ultraviolet lamp, the camera carries out real-time photographing, and information is transmitted to a mobile phone. And the fluorescence RGB value is calculated by using mobile phone color identification software, and then the concentration is detected, so that the real-time detection and recording of the color are realized.

The invention provides an image color recognition method, computer equipment and a storage medium, and the method comprises the steps: obtaining a to-be-recognized image, and extracting a sky region in the to-be-recognized image; a target color area is determined in the sky area, image features of the to-be-recognized image are determined based on the target color area and the sky area, and the color of the target color area is in a preset color interval; and when it is determined that the to-be-identified image satisfies a toning condition based on the image features, toning the sky area. In the embodiment of the invention, the influence of other area pixels, such as ground area pixels, in the to-be-identified image on image feature extraction is eliminated, so that the reliability of determining whether the to-be-identified image meets the toning condition or not based on the image features is improved, and when it is determined that the to-be-identified image meets the toning condition, the toning accuracy of the to-be-identified image is improved. And toning the sky area in the to-be-identified image, or not executing toning operation when the to-be-identified image does not meet the toning condition.