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32 results about "Gabor wavelet transform" patented technology
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Method and apparatus for image analysis of a gabor-wavelet transformed image using a neural network
The present invention may be embodied in a method, and in a related apparatus, for classifying a feature in an image frame. In the method, an original image frame having an array of pixels is transformed using Gabor-wavelet transformations to generate a transformed image frame. Each pixel of the transformed image is associated with a respective pixel of the original image frame and is represented by a predetermined number of wavelet component values. A pixel of the transformed image frame associated with the feature is selected for analysis. A neural network is provided that has an output and a predetermined number of inputs. Each input of the neural network is associated with a respective wavelet component value of the selected pixel. The neural network classifies the local feature based on the wavelet component values, and indicates a class of the feature at an output of the neural network.
Owner:GOOGLE LLC
Face recognition method based on Gabor wavelet transform and local binary pattern (LBP) optimization
InactiveCN102024141AReduce distractionsShort storage timeCharacter and pattern recognitionGabor wavelet transformHigh dimensional
The invention relates to a face recognition method based on Gabor wavelet transform and local binary pattern (LBP) optimization. Two-dimensional Gabor wavelet transform can associate pixels of adjacent areas so as to reflect the change conditions of image pixel gray values in a local range from different frequency scales and directions. The feature extraction and the classification recognition are carried out on the basis of a face image two-dimensional Gabor wavelet transform coefficient. For a high-dimensional Gabor wavelet transform coefficient, overall histogram features are extracted by adopting the LBP, and then the image is blocked by utilizing priori knowledge to extract the features of each piece of LBP local histogram. The method has better recognition rate, better robustness to illumination and wide using prospect in the fields of biometric recognition and public security monitoring.
Owner:SHANGHAI UNIV
Optical method and system for rapid identification of multiple refractive index materials using multiscale texture and color invariants
ActiveUS20050126505A1Rapid and accurate identificationRapid and accurate and classificationClimate change adaptationCharacter and pattern recognitionGabor wavelet transformFeature set
An innovative optical system and method is disclosed for analyzing and uniquely identifying high-order refractive indices samples in a diverse population of nearly identical samples. The system and method are particularly suitable for ultra-fine materials having similar color, shape and features which are difficult to identify through conventional chemical, physical, electrical or optical methods due to a lack of distinguishing features. The invention discloses a uniquely configured optical system which employs polarized sample light passing through a full wave compensation plate, a linear polarizer analyzer and a quarter wave retardation plate for producing vivid color bi-refringence pattern images which uniquely identify high-order refractive indices samples in a diverse population of nearly visually identical samples. The resultant patterns display very subtle differences between species which are frequently indiscernable by conventional microscopy methods. When these images are analyzed with a trainable with a statistical learning model, such as a soft-margin support vector machine with a Gaussian RBF kernel, good discrimination is obtained on a feature set extracted from Gabor wavelet transforms and color distribution angles of each image. By constraining the Gabor center frequencies to be low, the resulting system can attain classification accuracy in excess of 90% for vertically oriented images, and in excess of 80% for randomly oriented images.
Owner:WOODS HOLE OCEANOGRAPHIC INSTITUTION
Facial expression recognizing method based on Gabor transform optimal channel blur fusion
ActiveCN101872424AGive full play to the superiorityPlay a role in dimensionality reductionCharacter and pattern recognitionGabor wavelet transformGabor transform
The invention provides a facial expression recognizing method based on Gabor transform optimal channel blur fusion, comprising the following steps of: S1, dividing a Gabor filter into 11 channels, carrying out Gabor wavelet transform on a facial expression image subjected to normalization by the Gabor filter to extract texture characteristics of the facial expression image; S2, establishing classifiers corresponding to the channels one by one, respectively sending the texture characteristics extracted from the channels into the classifiers for classifying and recognizing, calculating the recognition rate and the definition of each classifier to various expressions, selecting 4 classifiers with top comprehensive ranking of the recognition rate and the definition to be used as optimal classifiers; and S3, carrying blur fusion on the four optimal classifiers to obtain a facial expression recognition result. The facial expression recognition method has the advantages of small calculated amount, high calculating speed and high recognition precision.
Owner:BEIJING PICOHOOD TECH
En-ULLELDA-based method of multi-view model recognition
InactiveCN101635027AImprove recognition rateCharacter and pattern recognitionGabor wavelet transformTest sample
The invention provides an En-ULLELDA-based (ensemble-unified locally linear embedding and linear discriminant analysis) method of multi-view model recognition. The method comprises the following steps: firstly, selecting a vehicle ROI (region of interest); secondly, extracting the high-level information that can reflect the model as features through Gabor wavelet transform; then, carrying out the dimension reduction of features on the basis of a novel manifold learning algorithm En-ULLELDA, so as to transform the features to a low-dimensional space; and obtaining the corresponding models from the features of a test sample by a classifier during the recognition. According to test results, the invention can effectively handle the problem of multi-view model recognition on urban roads; and the invention can eliminate the effects of parameter variation on the recognition results by employing the integration technology, so that the invention has higher robustness.
Owner:深圳市麟静科技有限公司
Remote sensing image variation detecting method on basis of weighted Gabor wavelet characteristics and two-stage clusters
InactiveCN103971364AEffective portrayalReduce the impactImage analysisState variationGabor wavelet transform
The invention discloses a remote sensing image variation detecting method on the basis of weighted Gabor wavelet characteristics and two-stage clusters. The processed objects include optical remote sensing images and SAR (synthetic aperture radar) images and the remote sensing image variation detecting method includes (1) generating difference images according to remote sensing image types; (2) subjecting the difference images to Gabor wavelet transform; (3) extracting multiscale and multidirectional characteristics of the Gabor wavelet transform of the difference images; (4) designing the weighting coefficient and acquiring the weighted Gabor wavelet characteristics; (5) clustering the weight Gabor wavelet characteristics by means of the two-stage cluster strategy; (6) acquiring variation detecting results. By the remote sensing image variation detecting method, loss of marginal information is reduced, stronger, weak and slight varying areas can be detected at the same time, the total mistake pixel number is decreased, more detail information is reserved and variation results can be effectively extracted.
Owner:SOUTHWEST JIAOTONG UNIV
Method and system for identifying human facial expression
InactiveCN102880862AReduce data processingRecognition time is shortCharacter and pattern recognitionInternal memoryGabor wavelet transform
The invention provides a method and a system for identifying human facial expression. The method for identifying the human facial expression comprises the steps of utilizing ASM (active shape model) algorithm to extract a shape model and feature points of a to-be-identified facial image, then, utilizing Gabor wavelet transform algorithm to extract amplitude texture characteristics of the feature points; obtaining a to-be-identified eigen face through projection for the amplitude texture characteristics; and identifying expression of a to-be-identified human face by comparing similarity between the to-be-identified eigen face and a sample eigen face. According to the method and the system for identifying human facial expression, the ASM algorithm is combined for extracting the feature points, so that identification through the Gabor wavelet transform algorithm can be performed only by comparing textural characteristics of the feature points. Compared with the existing facial identification technology only adopting the Gabor wavelet algorithm, the method and the system for identifying the human facial expression has the advantages of small data processing capacity, short identification time, low internal memory loss and the like.
Owner:TCL CORPORATION
Non-fluorescent eye fundus image based automatic segmentation method for retinal blood vessels
ActiveCN106355599AReduce segmentation errorEliminate distractionsImage enhancementImage analysisHysteresisPattern recognition
The invention relates to a non-fluorescent eye fundus image based automatic segmentation method for retinal blood vessels. The method comprises following steps: step one, an image is preprocessed, blood vessel characteristics are enhanced, and background noise is weakened; step two, morphological characteristics of the retinal image are extracted with a multi-scale linear operator, and a refined blood vessel framework is segmented with two-dimensional Gabor wavelet transform; step three, after the refined blood vessel framework is segmented, the image is subjected to path morphology filtering, the maximum path length is combined with geometrical characteristics of a blood vessel region, and an adjacent map is constructed; step four, a binaryzation process is performed with regional connectivity analysis and a hysteresis threshold technology for auxiliary segmentation of microvessels, and the segmentation is finished. Compared with the prior art, the method has the advantages as follows: the blood vessel location accuracy is higher, the adhesion phenomena are reduced, and a retinal blood vessel network of the eye fundus image is effectively segmented.
Owner:SHANGHAI JIAO TONG UNIV
GrabCut texture image segmentation method based on Gabor transform
InactiveCN106780508AAvoid paralysisImprove securityImage enhancementImage analysisGabor wavelet transformFrequency spectrum
The invention provides a GrabCut texture image segmentation method based on Gabor transform. The method comprises the following steps that: transforming a two-dimensional image into frequency domain space representation through Gabor wavelet transform, calculating the parametric transform of a frequency spectrum space two-dimensional Gabor filter group to obtain multi-scale multi-direction texture features, constructing a multi-scale texture energy generic function, calculating the GMM (Gaussian Mixture Model) probability distribution model of the texture features, and introducing the GMM of the texture features into GrabCut for image segmentation. The GrabCut texture image segmentation method based on the Gabor transform has the characteristics of being simple in artificial interaction, high in processing speed, good in image segmentation effect and the like.
Owner:BEIJING UNION UNIVERSITY
Multi-modal emotion analysis method and system based on deep learning for acupuncture
ActiveCN111881812AReduce typesReduce distractionsNeural architecturesAcquiring/recognising facial featuresGabor wavelet transformAcupuncture
The invention provides a multi-modal emotion analysis method and system based on deep learning for acupuncture, and belongs to the technical field of emotion recognition. According to the method, feature extraction is carried out on facial expression features by adopting Gabor wavelet transform, feature extraction and dimension reduction processing are carried out on electroencephalogram signals by adopting UPLBP, then sparse linear fusion is carried out on the facial expression features and the electroencephalogram signal features to fuse the facial expression features and the electroencephalogram signal features into a unified and normalized feature vector, and the feature vector is transformed into a tensor form; training is carried out in a CNN-LSTM network, redundant information is removed and predicted emotion classification information is obtained, and a loss function and a correct rate of the network ar calculated by comparing the predicted emotion classification information with actual emotion classification information. According to the invention, the expression features and the electroencephalogram signal features are fused, redundant information is removed, training isconducted through the CNN-LSTM network, the predicted emotion classification information is obtained, and the emotion recognition accuracy is improved.
Owner:INST OF ACUPUNCTURE & MOXIBUSTION CHINA ACADEMY OF CHINESE MEDICAL SCI
Multi-temporal high-resolution remote sensing image building extraction method based on multi-feature LSTM network
ActiveCN111582194AAccurate extractionGood outlineImage enhancementImage analysisConditional random fieldGabor wavelet transform
The invention discloses a multi-temporal high-resolution remote sensing image building extraction method based on a multi-feature LSTM network, and belongs to the technical field of satellite remote sensing image processing and application. The method aims to solve the problems of low accuracy, high error rate, fuzzy boundary and the like of a building extraction result of an existing method. According to the invention, a plurality of multi-temporal high-resolution No.2 remote sensing images are used as data sources; building spectral characteristics are extracted by using a method based on HSI color transformation; based on a method of combining graph segmentation and conditional random field post-processing, shape features of a building are extracted, based on a Gabor wavelet transform method, texture information features of the building are extracted, and based on a DSBI index method, index features of the building are extracted. A building characteristic set with 60 characteristicwave bands is formed by the extracted spectrum, shape, texture and index characteristics of the multi-temporal building, a manufactured building sample and a label are sent into an LSTM network to obtain a building coarse extraction result, and a final result is obtained after morphological processing.
Owner:JILIN UNIV
Image quality assessment method and device
InactiveCN106709916AReflect visual perceptionImprove forecast accuracyImage analysisCharacter and pattern recognitionGabor wavelet transformImaging quality
The invention relates to an image quality assessment method and an image quality assessment device. The method comprises the steps of acquiring a predetermined quantity of sample images, and extracting preset feature values in each sample image related to Gabor wavelet transform information, YCbCr color spatial feature information and MSCN coefficient statistical feature information of the sample image; training by using a support vector machine (SVM) method to acquire a SVM classifier according to the extracted preset feature values in each sample image; and receiving an input image, and assessing the input image according to the SVM classifier to acquire an assessment result. According to the method and the device provided by the invention, the visual perception effect of people on image quality can be accurately reflected, and image quality assessment prediction precision and accuracy can be improved.
Owner:TAIKANG LIFE INSURANCE CO LTD
Optical method and system for rapid identification of multiple refractive index materials using multiscale texture and color invariants
ActiveUS7415136B2Improve discriminationFinish quicklyClimate change adaptationCharacter and pattern recognitionGabor wavelet transformFeature set
An innovative optical system and method is disclosed for analyzing and uniquely identifying high-order refractive indices samples in a diverse population of nearly identical samples. The system and method are particularly suitable for ultra-fine materials having similar color, shape and features which are difficult to identify through conventional chemical, physical, electrical or optical methods due to a lack of distinguishing features. The invention discloses a uniquely configured optical system which employs polarized sample light passing through a full wave compensation plate, a linear polarizer analyzer and a quarter wave retardation plate for producing vivid color bi-refringence pattern images which uniquely identify high-order refractive indices samples in a diverse population of nearly visually identical samples. The resultant patterns display very subtle differences between species which are frequently indiscernable by conventional microscopy methods. When these images are analyzed with a trainable with a statistical learning model, such as a soft-margin support vector machine with a Gaussian RBF kernel, good discrimination is obtained on a feature set extracted from Gabor wavelet transforms and color distribution angles of each image. By constraining the Gabor center frequencies to be low, the resulting system can attain classification accuracy in excess of 90% for vertically oriented images, and in excess of 80% for randomly oriented images.
Owner:WOODS HOLE OCEANOGRAPHIC INSTITUTION
Device for detecting beef tenderness based on color image textural features and method thereof
InactiveCN103185731AAccurate predictionImprove forecast accuracyImage analysisMaterial analysis by optical meansColor imageCamera lens
The invention relates to a device for detecting beef tenderness based on color image textural features, which comprises a lamp box, a lighting system, a shooting system, an objective table and a computer, wherein the objective table is mounted at the bottom of the lamp box; the shooting system comprises a CCD digital camera and a camera bracket, the CCD digital camera is fixed on the camera bracket and mounted at the top of the lamp box; a lens of the CCD digital camera aims at center of the table board of the objective table; the computer is connected with the CCD digital camera; the lighting system comprises daylight lamp components and halogen lamp light source components; the daylight lamp components are mounted at the bottom of the objective table; and the halogen lamp light source components are mounted on two sides at the top of the lamp box. Through textural feature analysis, the device acquires a beef sample image, extracts parameters describing beef surface texture feature by adopting grayness symbiosis matrix, two-dimensional fast Fourier transform wavelet conversion and Gabor wavelet transform, so as to provide feature parameters for a tenderness predictive model, and utilizes stepwise regression and a support vector machine to predict the beef tenderness, with the predictive accuracy rate up to 100%.
Owner:NANJING AGRICULTURAL UNIVERSITY
A facial expression recognition feature extraction algorithm based on the Weber multi-direction descriptor
ActiveCN108090460AImprove recognition rateReduce feature dimensionAcquiring/recognising facial featuresImaging processingGabor wavelet transform
Owner:TIANJIN UNIVERSITY OF SCIENCE AND TECHNOLOGY
Forming method and system of facial expression intensity calculation model
InactiveCN107895154AStrength gainAcquiring/recognising facial featuresGabor wavelet transformComputational model
The invention provides a forming method and a system of a facial expression intensity calculation model. The model is used for estimating the facial expression intensity under expression classification. The method comprises the steps of acquiring an expression database firstly, preprocessing image data in the expression database, extracting the data of a face part, performing feature extraction inthe three modes of face geometric features, local binary patterns and Gabor wavelet transform respectively, training data outputted in the previous step respectively in the full-supervision mode, thesemi-supervised mode and the non-supervision mode so as to obtain the relation between a feature and a facial expression intensity, respectively adopting trained data as the input of an ordinal random forest algorithm to train the data and respectively obtain facial expression intensity calculation sub-models, and forming a final facial expression intensity calculation model according to each ofthe sub-models. According to the invention, the facial expression intensity calculation model under the expression classification is trained by means of the database. The model is used for processingimage data, so that the intensity under the trained expression classification can be obtained.
Owner:CHINA UNIV OF GEOSCIENCES (WUHAN)
Face recognition method and device
ActiveCN102750523AAvoid the problem of discrete directionsReduce redundancyCharacter and pattern recognitionImaging processingGabor wavelet transform
The invention is applicable to the field of image processing, and provides face recognition method and device. The method comprises the steps: generating a plurality of test subimages from a test image by circularly symmetrical gabor transformation; blocking each test subimage to obtain a corresponding test subimage matrix, and respectively projecting each test subimage to a corresponding sample feature face space to obtain a corresponding test face feature space; respectively calculating Euclid distances of the test face feature spaces and those of the sample face feature spaces to recognize the similarity of a sample image and the test image. The circularly symmetrical gabor transformation has rotation without deformation, thus avoiding the direction discretion problem caused by adopting traditional gabor wavelet transformation, and obviously reducing redundancy. In addition, the high-dimensional test image is projected to the low-dimensional sample feature face space for recognition, thus greatly reducing the calculation complexity and improving the recognition property.
Owner:TCL CORPORATION
Face feature-based gender classifying method and device
The invention discloses a face feature-based gender classifying method and a face feature-based gender classifying device. The face feature-based gender classifying method comprises the following steps: preprocessing a face image based on eye positioning coordinates; performing image scaling on the face image to form a multi-resolution Gaussian pyramid; performing Gabor wavelet transform for different scales and directions; performing local binary pattern transformation on the Gabor face image, and equably dividing the face image in horizontal and vertical directions; extracting histogram dataof each region of the Gabor local binary pattern face image; acquiring sample data with male and female tags in multi-resolution local Gabor binary pattern MLGBP features, and reducing the dimensionof a central connecting line for a feature vector of each divided region; training in a gender classifying model based on a support vector machine to obtain the gender classifying model; inputting thefeatures into the gender classifying model to obtain an analysis result.
Owner:深圳市车顶传媒有限公司
Front gait recognition method based on feature fusion
PendingCN112633058AReduce data volumeWell representedCharacter and pattern recognitionHuman bodyGabor wavelet transform
A front gait recognition method based on feature fusion belongs to the technical field of mode recognition. The method mainly aims at solving the problem that the gait recognition rate of a single feature is low, firstly, a dynamic region in a gait energy diagram is extracted, features are extracted through Gabor wavelet transform, dimension reduction processing needs to be conducted due to the fact that the extracted features are high in dimension, and for the defect that traditional PCA dimension reduction classification is poor, dimension-reduced data serve as static features. The gait period is obtained according to the change of the ratio of the number of pixel points on the left side to the number of pixel points on the right side of the lower quarter area of the human body and used for describing the dynamic characteristics of the gait sequence, and based on the idea of characteristic fusion, static data characteristics obtained after PCA and LDA dimension reduction are fused with the dynamic characteristics describing the gait sequence for the first time; and finally, inputting the fused feature vectors into a support vector machine based on multi-classification to finish gait classification and recognition. Compared with a gait recognition method with a single feature, the fusion algorithm provided by the invention shows better recognition performance.
Owner:BEIJING UNIV OF TECH
Deep learning-based multimodal emotion analysis method and system for acupuncture and moxibustion
ActiveCN111881812BReduce typesReduce distractionsNeural architecturesAcquiring/recognising facial featuresGabor wavelet transformFeature extraction
The invention provides a deep learning-based multimodal emotion analysis method and system for acupuncture and moxibustion, belonging to the technical field of emotion recognition. The present invention uses Gabor wavelet transform for feature extraction on facial expression features, uses UPLBP to perform feature extraction on EEG signals, performs dimensionality reduction processing, and then uses sparse linear fusion of facial expression features and EEG signal features to form a unified , normalized eigenvectors, and transform eigenvectors into tensor form, input CNN‑LSTM network for training, remove redundant information and obtain predicted emotion classification information, and calculate network loss by comparing predicted emotion classification information with actual emotion classification information function and accuracy. The present invention fuses expression features and EEG signal features, removes redundant information, and obtains predicted emotion classification information through CNN-LSTM network training, thereby improving the accuracy of emotion recognition.
Owner:INST OF ACUPUNCTURE & MOXIBUSTION CHINA ACADEMY OF CHINESE MEDICAL SCI
Facial expression recognizing method based on Gabor transform optimal channel blur fusion
ActiveCN101872424BGive full play to the superiorityPlay a role in dimensionality reductionCharacter and pattern recognitionGabor wavelet transformRanking
The invention provides a facial expression recognizing method based on Gabor transform optimal channel blur fusion, comprising the following steps of: S1, dividing a Gabor filter into 11 channels, carrying out Gabor wavelet transform on a facial expression image subjected to normalization by the Gabor filter to extract texture characteristics of the facial expression image; S2, establishing classifiers corresponding to the channels one by one, respectively sending the texture characteristics extracted from the channels into the classifiers for classifying and recognizing, calculating the recognition rate and the definition of each classifier to various expressions, selecting 4 classifiers with top comprehensive ranking of the recognition rate and the definition to be used as optimal classifiers; and S3, carrying blur fusion on the four optimal classifiers to obtain a facial expression recognition result. The facial expression recognition method has the advantages of small calculated amount, high calculating speed and high recognition precision.
Owner:BEIJING PICOHOOD TECH
Automatic retinal vessel segmentation method based on non-fluorescent fundus images
ActiveCN106355599BEffective segmentationReduce noise interferenceImage enhancementImage analysisPattern recognitionHysteresis
The invention relates to a non-fluorescent eye fundus image based automatic segmentation method for retinal blood vessels. The method comprises following steps: step one, an image is preprocessed, blood vessel characteristics are enhanced, and background noise is weakened; step two, morphological characteristics of the retinal image are extracted with a multi-scale linear operator, and a refined blood vessel framework is segmented with two-dimensional Gabor wavelet transform; step three, after the refined blood vessel framework is segmented, the image is subjected to path morphology filtering, the maximum path length is combined with geometrical characteristics of a blood vessel region, and an adjacent map is constructed; step four, a binaryzation process is performed with regional connectivity analysis and a hysteresis threshold technology for auxiliary segmentation of microvessels, and the segmentation is finished. Compared with the prior art, the method has the advantages as follows: the blood vessel location accuracy is higher, the adhesion phenomena are reduced, and a retinal blood vessel network of the eye fundus image is effectively segmented.
Owner:SHANGHAI JIAOTONG UNIV
Building extraction method of multi-temporal high-resolution remote sensing images based on multi-feature lstm network
ActiveCN111582194BAccurate extractionGood outlineImage enhancementImage analysisConditional random fieldGabor wavelet transform
The invention discloses a multi-temporal high-resolution remote sensing image building extraction method based on a multi-feature LSTM network, which belongs to the technical field of satellite remote sensing image processing and application. The purpose is to solve the problems of low accuracy rate, high misclassification rate and blurred boundary of building extraction results in existing methods. The present invention uses multiple multi-temporal Gaofen No. 2 remote sensing images as the data source, uses the method based on HSI color transformation to extract the spectral features of the building, and extracts the shape features of the building based on the method of combining image segmentation and conditional random field post-processing. The method based on Gabor wavelet transform to extract the texture information features of the building and the method based on the DSBI index to extract the index features of the building, and the extracted spectrum, shape, texture and index features of the multi-temporal buildings are composed of 60 feature bands The building feature set, and the produced building samples and labels are sent to the LSTM network to obtain the rough extraction results of the buildings, and the final results are obtained after morphological processing.
Owner:JILIN UNIV
A method and system for recognizing facial expressions
InactiveCN102880862BReduce data processingRecognition time is shortCharacter and pattern recognitionInternal memoryGabor wavelet transform
The invention provides a method and a system for identifying human facial expression. The method for identifying the human facial expression comprises the steps of utilizing ASM (active shape model) algorithm to extract a shape model and feature points of a to-be-identified facial image, then, utilizing Gabor wavelet transform algorithm to extract amplitude texture characteristics of the feature points; obtaining a to-be-identified eigen face through projection for the amplitude texture characteristics; and identifying expression of a to-be-identified human face by comparing similarity between the to-be-identified eigen face and a sample eigen face. According to the method and the system for identifying human facial expression, the ASM algorithm is combined for extracting the feature points, so that identification through the Gabor wavelet transform algorithm can be performed only by comparing textural characteristics of the feature points. Compared with the existing facial identification technology only adopting the Gabor wavelet algorithm, the method and the system for identifying the human facial expression has the advantages of small data processing capacity, short identification time, low internal memory loss and the like.
Owner:TCL CORPORATION
Facial expression recognition method and device based on Gabor wavelets
PendingCN112084888AReduce distractionsImprove recognition rateAcquiring/recognising facial featuresFeature vectorGabor wavelet transform
The invention discloses a facial expression recognition method and device based on Gabor wavelets. The method comprises the following steps: carrying out graying and size normalization processing on an input image; according to a preset gray average value and a gray variance, carrying out gray equalization processing on the image after graying and size normalization processing, and the image aftergray equalization processing is used as a to-be-identified image; carrying out Gabor wavelet transform on the image to be identified by adopting a two-dimensional Gabor wavelet filter bank; extracting an expression feature vector of the to-be-recognized image; and carrying out matching identification on the extracted expression feature vector by using a non-uniform elastic grid template. The device comprises a preprocessing module, a feature extraction module and an identification matching module. According to the invention, the Gabor wavelet filtering is improved, the interference is effectively reduced, the recognition rate is greatly improved, and the operation time is greatly reduced.
Owner:BEIJING YINGPU TECH CO LTD
Face feature and dynamic attribute authentication method based on WeChat applet platform
ActiveCN111460416AImprove securityImprove reliabilityCharacter and pattern recognitionDigital data authenticationGabor wavelet transformPassword
Owner:YANGO UNIV
Multi-view model recognition method based on integrated local linear embedding and linear discrimination analysis
InactiveCN101635027BImprove recognition rateCharacter and pattern recognitionPattern recognitionGabor wavelet transform
Owner:深圳市麟静科技有限公司
Recognition method of proximal interphalangeal joint texture based on gabor wavelet
InactiveCN107688787BImprove securityEnsure safetyCharacter and pattern recognitionLittle fingerGabor wavelet transform
The invention utilizes Gabor wavelet decomposition to extract the texture features of the interphalangeal joints of four fingers (index finger, middle finger, ring finger and little finger). Feature extraction will eventually result in a covariance matrix between Gabor wavelet subbands. The covariance matrix can describe the correlation structure between the Gabor wavelet subbands, and it has better discrimination than calculating the subband variance in an independent way; the identification part is to compare the current acquisition identity Gabor subband covariance matrix with the memory Comparison between Gabor subband covariance matrices of registered identities. In order to improve the performance, the Gabor wavelet sub-band is firstly transformed by CDF (cumulative distribution function), and then the transformed result is calculated. Main features of the present invention: (1) The identification method has high security, and the characteristics of the four fingerprints ensure the security of the system; (2) It has good resistance to noise, and Gabor wavelet transform and CDF projection can effectively resist image noise interference .
Owner:YIBIN UNIV
Texture compression method and device of three-dimensional map image
The embodiment of the invention discloses a texture compression method and device of a three-dimensional map image. The method comprises a step of dividing a target texture image into blocks, a step of extracting the characteristic of each block through two-dimensional Gabor wavelet transform, a step of clustering each block of the target texture image according to the Euclidean distance between the features of different blocks, and a step of substituting other blocks in the same class by one block in the blocks belonging to the same class after clustering. According to the texture compression method and device of a three-dimensional map image provided by the embodiment of the invention, the effective compression of the texture image in the three-dimensional map is realized.
Owner:BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
Method and system for forming facial expression intensity calculation model
InactiveCN107895154BStrength gainAcquiring/recognising facial featuresGabor wavelet transformFeature extraction
A method and system for forming a facial expression intensity calculation model. The model is used to estimate the facial expression intensity under expression classification. First, an expression database is obtained, image data in the expression database are preprocessed, and facial part data is extracted. The feature extraction of the three modes of facial geometric features, local binary mode and Gabor wavelet transform is carried out respectively, and the data output in the previous step are trained by using the fully supervised mode, semi-supervised mode and unsupervised mode respectively, and the features and facial expression strength are obtained The data formed after training are respectively used as the input of the ordinal random forest algorithm for training, and the facial expression intensity calculation sub-models are respectively obtained, and the final facial expression intensity calculation model is formed according to each sub-model. The invention utilizes the database to train the facial expression intensity calculation model under the expression classification, and uses the model to process the image data to obtain the intensity under the trained expression classification.
Owner:CHINA UNIV OF GEOSCIENCES (WUHAN)
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