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203 results about "Level set function" patented technology
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Level Set. The level set of a differentiable function corresponding to a real value is the set of points. For example, the level set of the function corresponding to the value is the sphere with center and radius . If , the level set is a plane curve known as a level curve.
Method for time-evolving rectilinear contours representing photo masks
InactiveUS7124394B1Originals for photomechanical treatmentSoftware simulation/interpretation/emulationPattern recognitionMerit function
Photomask patterns are represented using contours defined by level-set functions. Given target pattern, contours are optimized such that defined photomask, when used in photolithographic process, prints wafer pattern faithful to target pattern. Optimization utilizes “merit function” for encoding aspects of photolithographic process, preferences relating to resulting pattern (e.g. restriction to rectilinear patterns), robustness against process variations, as well as restrictions imposed relating to practical and economic manufacturability of photomasks.
Owner:KLA TENCOR TECH CORP
Optimized photomasks for photolithography
InactiveUS7480889B2Character and pattern recognitionCAD circuit designPattern recognitionComputer science
Owner:KLA CORP
System and method for global-to-local shape matching for automatic liver segmentation in medical imaging
ActiveUS20090052756A1Improve robustnessPreserve topologyImage enhancementImage analysisIntensity histogramMedical imaging
A method for automatically segmenting a liver in digital medical images includes providing a 3-dimensional (3D) digital image I and a set of N training shapes {φi}i=1, . . . , N for a liver trained from a set of manually segmented images, selecting a seed point to initialize the segmentation, representing a level set function φα(θx+h) of a liver boundary Γ in the image asφα(x)=φ0+∑i=1nαiVi(x),whereφ0(x)=1N∑i=1Nφi(x)is a mean shape, {Vi(x)}i=1, . . . , n are eigenmodes where n<N, αi are shape parameters, and h ε R3 and θε [0,2π]3 are translation and rotation parameters that align the training shapes, minimizing a first energy functional to determine the shape, translation, and rotation parameters to determine a shape template for the liver segmentation, defining a second energy functional of the shape template and a registration mapping weighted by image intensity histogram functions inside and outside the boundary, and minimizing the second energy functional to determine the registration mapping, where the registration mapping recovers local deformations of the liver.
Owner:SIEMENS HEALTHCARE GMBH
High resolution ratio remote-sensing image division and classification and variety detection integration method
InactiveCN101126812ASimple methodFew parametersElectromagnetic wave reradiationLand resourcesHazard monitoring
The utility model discloses a integrated method based on multi-level set evolution and high resolution remote sensing image partition, classification and change inspection, which is characterized in that (1) image preprocessing (radiation, registration and filtering); (2) the multi-level set evolutional partition and classification model, after registration, the GIS data determines the initial profile of each level set function and performs the partition and classification to the first phase image; (3) the model described in the (2) is still adopted, and the initial profile of each level set function is optimized, increment type partition and classification is adopted for the second to T phase; (4) the objective after partition is used as unit, the ith and (i+1)th two adjacent phase image classification results are compared to determine the change area; (5) return back to (3) until the partition, classification and change inspection of all T phase image are finished. The utility model has the advantages that: compared with the traditional pixel-oriented K value method, the classification and inspection precision are improved, The utility model is applicable for the change inspection of sequence remote sensing image and has wide application in hazard monitoring and land resource investigation.
Owner:WUHAN UNIV
Structural optimization system, structural optimization methodlogy, and structural optimization program
ActiveUS20110270587A1Increase freedomGeometric CADDesign optimisation/simulationDegrees of freedomEngineering
The present invention enables a shape of an optimum structure to be clearly represented, and structural optimization having a high degree of freedom such as the allowance of a change in topology in a material domain Ω to be performed. The present invention sets a level set function φ; under a predetermined constraint condition, updates the level set function φ so as to bring a performance of a structure, such as a rigidity, close to a target value; moves a boundary ∂Ω between the material domain Ω and a void domain; allows a change in topology in the material domain Ω, which is associated with the update of the level set function φ, to form a new void domain in the material domain Ω; and moves a boundary ∂Ω between the new void domain and the material domain Ω.
Owner:KYOTO UNIV
Method for segmenting image with non-uniform gray scale based on level set function
InactiveCN102354396AImprove accuracyImprove efficiencyImage enhancementEnergy functionalComputer vision
The invention provides a method for segmenting an image with non-uniform gray scale based on a level set function. The method comprises the following steps: constructing the level set function; constructing image segmentation energy functional; and carrying out level set function evolution so that the energy functional is minimized so as to obtain an image segmentation boundary, wherein, the energy functional comprises a global energy statistical item, a local energy statistical item and an energy penalty item. In the invention, on the basis of a C-V (Chan-Vese) model, a Gaussian kernel function is introduced and the local statistical information for the image with the non-uniform gray scale is fully utilized so as to optimize the 'energy' functional for a minimized closed curve; and by adding the energy penalty item, convergence of a signed distance function (SDF) is ensured and the time-consuming reinitialization process is avoided. Experiments prove that by adopting the method for segmenting the image with the non-uniform gray scale, clear and accurate segmentation results can be obtained and the segmentation accuracy and efficiency for the image with the non-uniform gray scale can be improved.
Owner:SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
Optimized photomasks for photolithography
ActiveUS20070011644A1Character and pattern recognitionCAD circuit designPattern recognitionPhotolithography
Photomask patterns are represented using contours defined by level-set functions. Given target pattern, contours are optimized such that defined photomask, when used in photolithographic process, prints wafer pattern faithful to target pattern. Optimization utilizes “merit function” for encoding aspects of photolithographic process, preferences relating to resulting pattern (e.g. restriction to rectilinear patterns), robustness against process variations, as well as restrictions imposed relating to practical and economic manufacturability of photomasks.
Owner:KLA TENCOR TECH CORP
Optimized photomasks for photolithography
InactiveUS20070011647A1Character and pattern recognitionComputation using non-denominational number representationPattern recognitionPhotolithography
Photomask patterns are represented using contours defined by level-set functions. Given target pattern, contours are optimized such that defined photomask, when used in photolithographic process, prints wafer pattern faithful to target pattern. Optimization utilizes “merit function” for encoding aspects of photolithographic process, preferences relating to resulting pattern (e.g. restriction to rectilinear patterns), robustness against process variations, as well as restrictions imposed relating to practical and economic manufacturability of photomasks.
Owner:DINO TECH ACQUISITION
Determining Source Patterns for Use in Photolithography
ActiveUS20110022994A1Increased process windowPhotomechanical apparatusOriginals for photomechanical treatmentPattern recognitionLithographic artist
Embodiments of a computer system, a process, a computer-program product (i.e., software), and a data structure or a file for use with the computer system are described. These embodiments may be used to determine or generate source patterns that define illumination patterns on photo-masks during a photolithographic process. Moreover, a given source pattern may be determined concurrently with an associated mask pattern (to which a given photo-mask corresponds) or sequentially (i.e., either the given source pattern may be determined before the associated mask pattern or vice versa.). During the determining, the given source pattern may be represented using one or more level-set functions. Additionally, the source pattern may be determined using an Inverse Lithography (ILT) calculation.
Owner:SYNOPSYS INC
System and method for fast tensor field segmentation
InactiveUS20060158447A1Facilitates efficient segmentationImage enhancementImage analysisDiffusionEnergy functional
Segmenting a digitized image includes providing a diffusion tensor field image, partitioning the image into 2 regions, each point being assigned to one of the regions, associating a level-set function with each region, the level-set function having a negative value in one region and a positive value in the other region, calculating a mean value of the diffusion tensor field over each of 2 regions, initializing an energy defined as a functional of level-set functions and diffusion tensor field, changing the region membership of each point in the image if the energy functional value decreases as a result of region membership change and updating said mean value of said diffusion tensor field over each of 2 regions, and obtaining a segmentation of the image when the magnitude of the change of the energy function value resulting from changing the region membership of a point is less then a predetermined threshold.
Owner:SIEMENS MEDICAL SOLUTIONS USA INC
An object segmentation method based on prior shape and cv model
The invention relates to an object segmentation method based on a priori shape and a CV (Computer Vision) model. The method comprises the following steps of: constructing a signed distance function by selecting the priori shape; carrying out affine transformation on the signed distance function of the priori shape according to vectors of affine transformation parameters, wherein the affine transformation parameters are changed and finally tend to stabilize in the process of iterating a level set function; and finally, obtaining various affine transformation parameters of the next time according to a level set iteration formula evolution movable outline curved line and various affine parameter iteration formulae. According to the method disclosed by the invention, on the basis of keeping rotary, zoom and translation invariance of a priori shape model, stretching in X and Y directions and shear unchanged constraint energy item can be increased; and a space object with larger posture transformation under a complex background can be well segmented by expanding the self-adaptive transformation of the priori shape.
Owner:SHANGHAI JIAO TONG UNIV
Three-dimensional lung vessel image segmentation method based on geometric deformation model
InactiveCN102243759AAccurate segmentationQuick splitImage analysis3D modellingRegion selectionImage gradient
The invention provides a three-dimensional lung vessel image segmentation method based on a geometric deformation model. The method comprises the following steps: (1) determining vessel segmentation computing regions according to the physiological structure characteristics of a human body, wherein region selection completely covers targets to be segmented and the shape characteristics of the regions are stable, thereby avoiding computing a global region and improving segmentation speed; (2) computing the mean value of the vessel regions and positioning internal and external homogeneous regions of the targets; (3) computing vessel edge energy and evolving a curved surface along second derivatives in an image gradient direction so that the curved surface is accurately converged to a target edge; (4) correspondingly establishing a three-dimensional vessel segmentation curved surface evolution model and effectively combining the mean value and edge energy of the internal and external regions of the lung vessels; and (5) adopting optimized level set evolution for obtaining solution according to the established deformation model and impliedly solving a curved surface motion according to the level set function curved surface evolution. A large quantity of lung CT image experiments proof that the method provided by the invention has the advantages of rapid and accurate lung vessel segmentation and strong robustness.
Owner:NORTHEASTERN UNIV
Level set SAR (Synthetic Aperture Radar) image segmentation method by combining edges and regional probability density difference
ActiveCN101976445AImprove segmentationImprove robustnessImage analysisCharacter and pattern recognitionPattern recognitionImaging processing
The invention discloses a level set SAR (Synthetic Aperture Radar) image segmentation method by combining edges and a regional probability density difference, belonging to the technical field of image processing and mainly solving the problems of difficult segmentation of SAR images with fuzzy edges and inaccurate positioning to real edges of the SAR images, of the traditional level set method. The method comprises the following implementation steps of: firstly, detecting an edge intensity modulus absolute value of Rmax of an SAR image by applying an ROEW operator; secondly, initializing a level set function phi, segmenting the SAR image into an inner region omega1 and an outer region omega2, and solving for the intensity mean values c1 and c2 of the two regions; thirdly, solving for the estimated probability densities of the two regions omega1 and omega2 according to c1 and c2 and calculating the actual probability densities p1 and p2 of the two regions; and fourthly, constructing a total energy function ESAR, solving for a gradient downstream equation by applying a variational method, and updating the level set phi to obtain new segmentation regions omega1 and omega2. Indicated by experimental results, the segmentation method can be used for obtaining more ideal segmentation effect and be used for the edge detection and the target identification of the SAR images.
Owner:XIDIAN UNIV
Level set retinal vessel image segmentation method with shape prior being fused
The invention relates to a level set retinal vessel image segmentation method with shape prior being fused. The method comprises the following steps: 1) enhancing a retinal vessel image by utilizing a morphological operator and through Gaussian convolution; 2) roughly segmenting the retinal vessel image through anisotropic property of a Hessian matrix and an improved vessel response function, and serving the images as shape constrains and initial information; and 3) constructing a retinal vessel segmentation level set model comprising a local area energy fitting item, a shape constraint item, a level set function regularity maintenance item, a length punishment item and a weight area restraint item by utilizing shape prior and retinal image data. The segmentation method is high in segmentation result accuracy, can replace manual segmentation, and can play an important helping role in diagnosis and treatment of clinical related eye diseases, and has a higher clinical application value.
Owner:JIANGXI UNIV OF SCI & TECH
System and method for global-to-local shape matching for automatic liver segmentation in medical imaging
ActiveUS8131038B2Improve robustnessPreserve topologyImage enhancementImage analysisIntensity histogramMedical imaging
A method for automatically segmenting a liver in digital medical images includes providing a 3-dimensional (3D) digital image I and a set of N training shapes {φi}i=1, . . . , N for a liver trained from a set of manually segmented images, selecting a seed point to initialize the segmentation, representing a level set function φα(θx+h) of a liver boundary Γ in the image asϕα(x)=ϕ0+∑i=1nαiVi(x),whereϕ0(x)=1N∑i=1Nϕi(x)is a mean shape, {Vi(x)}i=1, . . . , n are eigenmodes where n<N, αi are shape parameters, and h ε R3 and θε [0,2π]3 are translation and rotation parameters that align the training shapes, minimizing a first energy functional to determine the shape, translation, and rotation parameters to determine a shape template for the liver segmentation, defining a second energy functional of the shape template and a registration mapping weighted by image intensity histogram functions inside and outside the boundary, and minimizing the second energy functional to determine the registration mapping, where the registration mapping recovers local deformations of the liver.
Owner:SIEMENS HEALTHCARE GMBH
Method And Device For Continuous Figure-Ground Segregation In Images From Dynamic Visual Scenes
ActiveUS20090129675A1Speed up the processColor television with pulse code modulationImage analysisGraphicsMotion estimate
A method for segregating a figure region from a background region in image sequences from dynamic visual scenes, comprising the steps of: (a) acquiring an image; (b) determining local motion estimations and confidences for each position of the image; (c) modifying a level-set function by moving and distorting the level-set function with the local motion estimations and smearing it based on the local motion confidences, to generate a predicted level set function that is geometrically in correspondence with the image and diffused at positions where the confidence of the motion estimation is low; (d) obtaining input features of the image by using a series of cues; (e) calculating a mask segregating the figure region from the background region of the image using the modified level-set function and the obtained input features; (f) extracting the figure region from the image; and repeating steps (a)-(f) until a termination criterion is satisfied.
Owner:HONDA RES INST EUROPE
Auroral oval segmenting method based on brightness self-adaptive level set
InactiveCN102930273AImprove shape featuresAchieve precise segmentationCharacter and pattern recognitionPattern recognitionSaliency map
The invention discloses an auroral oval segmenting method based on a brightness self-adaptive level set, which mainly solves the defects of the existing auroral oval segmenting method that the segmentation precision is low, the robustness is poor and the application range is small. The auroral oval segmenting method comprises the following steps of (1) adopting a morphology component analysis method to preprocess an ultraviolet aurora image; (2) establishing a morphology saliency map to be used as shape characteristics of the auroral oval; (3) utilizing the marginal curve of the morphology saliency map to initialize a level set function; (4) calculating the brightness self-adaptive level set evolution speed and a stop function; (5) updating the level set function according to the brightness self-adaptive level set evolution equation; and (6) extracting a zero level set curve after being updated and utilizing the zero level set curve as the auroral oval margin to be outputted. Due to adopting the auroral oval segmenting method, the phenomenon of the traditional segmenting method such as result deviation and margin leakage can be avoided, advantages such as high segmentation precision and strong robustness can be achieved, and the method is applicable to the segmentation of different ultraviolet auroral images.
Owner:XIDIAN UNIV
Level set SAR image segmentation method based on local and global area information
ActiveCN102426700AEnough to split the edgesThe segmentation result is accurateImage enhancementSynthetic aperture radarGoal recognition
The invention discloses a level set SAR (Synthetic Aperture Radar) image segmentation method based on local and global area information, which mainly solves the problem that the existing level set method is influenced by speckle and cannot segment the SAR images with uneven gray. The method comprises the following implementation steps of: firstly, initializing a level set function phi, and segmenting the SAR image into an internal area omega 1 and an external area omega 2; secondly, convolving intensity information of the internal area and the external area of the image through a Gaussian Kernel Function, taking the convolved information as local area information, and forming an energy term based on the local area; then, solving intensity mean values c1 and c2 and probability densities p1and p2 of the internal area and the external area, and forming the energy term of the global area; and finally, adding a bound term L (phi) of level set length and a penalty P (phi) which avoids renewed initialization, forming a total energy function ESAR, solving a gradient sinking equation through a variation method, and updating the level set phi. The obtained new segmented area and the experimental result show that the segmentation method provided by the invention can get more ideal segmentation effects, and the method can be used for SAR image segmentation and target identification.
Owner:XIDIAN UNIV
Time-optimal route planning method based on improved level set algorithm
ActiveCN106503837ATake advantage ofEffectively foundForecastingGeographical information databasesAnalysis dataRoute planning
Owner:HARBIN ENG UNIV
Unsteady measurement algorithm based image segmentation method of improved rule distance level set
The invention discloses an unsteady measurement algorithm based image segmentation method of an improved rule distance level set, belongs to the field of digital image processing and aims to more precisely segment images of gaussian noise and salt and pepper noise interference. The method includes: firstly, constructing a mean operator, and setting a stopping function by the constructed operator; secondly, manually setting an initial contour, and initializing a level set function according to the contour; and thirdly, importing the stopping function set in the first step into an energy equation of a DRLSE model, minimizing the energy equation by the aid of a central difference method, and iterating by taking the initialized level set obtained in the second step as an initial condition to obtain a zero level set of a steady state solution, namely the final segmentation results. The method is more precise in segmentation of the images of the gaussian noise and salt and pepper noise interference as compared with a traditional geometric Snake model method.
Owner:HARBIN INST OF TECH
Particle image velocimetry (PIV) processing method
InactiveCN101629966AHigh precisionSuppress noiseFluid speed measurementComplex mathematical operationsMotion fieldOmega
The invention discloses a particle image velocimetry (PIV) processing method comprising the following steps: A. constructing a level set function phi in an N*M pixel range omega, wherein the level set function phi is a continuous function defined in the N*M pixel range omega; dividing the range omega into a first subregion omega1 and a second subregion omega2 so that a motion field, a divergence field and a rotation field are smoothly connected in the two subregions of omega1 and omega2, but are not continuous on the boundary, wherein a region where the phi is larger than or equal to 0 corresponds to the first subregion omega1, and a region where the phi is smaller than 0 corresponds to the second subregion omega2; B. constructing an energy function E=E1+lambda *E2 of the range omega:, wherein the E is a global energy functional, the E1 is data constraint energy, and the E2 is smooth constraint energy; and C. minimizing the global energy functional to realize the optimal approximation of the motion field, the divergence field and the rotation field. The invention provides the PIV processing method with high precision and good reliability.
Owner:SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
Method for effectively segmenting hyperspectral oil-spill image
InactiveCN106447688AImprove Segmentation AccuracyAccurate segmentationImage enhancementImage analysisBoundary contourEuler–Lagrange equation
Provided is a method for effectively segmenting a hyperspectral oil-spill image. The method comprises steps of: defining an initial level set function and other related functions; acquiring a new fitting item in combination with a Fisher criterion; constructing an edge stop function to obtain a new length item; performing improvement in combination with an end member extraction algorithm; introducing a level set regular item to prevent reinitialization of the level set function; minimizing an energy function to obtain an Euler-Lagrange equation; setting parameters; selecting a display band and an initial contour; displaying a segmentation result graph; calculating various segmentation precision evaluation indexes; comparing and evaluating the accuracy of the segmentation results. The method can classify a target area in a simulated hyperspectral image and a real hyperspectral image, and effectively segments the hyperspectral oil-spill image with boundary blur and noise, improves the segmentation accuracy of the hyperspectral image, obtain a more accurate classification effect, makes the parameter change more stable, makes the contour curve more accurate, obtains the continuous and closed boundary contour, and has higher precision of segmentation.
Owner:DALIAN MARITIME UNIVERSITY
Image segmentation active contour method based on global and local information self-adaptive adjustment
InactiveCN105551054AGuaranteed treatment effectGuaranteed stabilityImage enhancementImage analysisPattern recognitionGray level
The invention provides an image segmentation active contour method based on global and local information self-adaptive adjustment. The method comprises the following steps of (1) defining a novel self-adaptive balance function, wherein the weight of each part can be automatically regulated by using the novel self-adaptive balance function according to the self characteristics of an image, and further the curve evolution is driven; (2) in a weight function, adding a Gaussian filter process for regularizing a level set function, and meanwhile, adding a decreasing factor for accelerating the curve evolution speed; and (3) ensuring the precise calculation and the stable evolution of a model through introducing a penalty term. The method has the advantages that good segmentation effects are achieved on the segmentation precision and the processing speed; and the segmentation on a heterogeneous image with nonuniform gray level distribution can be realized.
Owner:LIAONING NORMAL UNIVERSITY
Mould cavity numerical control machining spiral curve track planning method
InactiveCN101452284AControl residual heightImprove processing efficiencyProgramme controlComputer controlNumerical controlVelocity function
The invention relates to a method for programming a spiral curve track through die cavity numerical control machining .The boundary of a die cavity is embedded into a level set function of a high one-dimensional space; a zero level set of the level set function is the boundary of the die cavity; and the level set function is initialized to a sign distance function. Bias of the boundary of the die cavity is obtained through the solution of a level set equation; and a speed function of the level set equation is corrected so that a high-curvature region can be smooth in generating a bias line. The distance between the bias lines is controlled through the control of time for boosting the boundary; in the process of boosting the boundary of the die cavity, the complex topological change is naturally treated; and the spiral curve track is programmed in different regions respectively. The method is suitable for programming a cutter track of a numerical control machining system with a common die cavity and a complex die cavity; the cutter track is continuous and smooth; and for the complex die cavity with island, the method can realize automatic division in regions and carry out spiral curve track programming in different regions.
Owner:SHANGHAI JIAO TONG UNIV
Efficient structure frequency response topological optimization method
InactiveCN107315872AFrequency Response Topology Optimization Method for Efficient StructuresGuaranteed smoothnessDesign optimisation/simulationSpecial data processing applicationsDynamic modelsElement analysis
The invention belongs to the technical field related to structure topological optimization design, and discloses an efficient structure frequency response topological optimization method. The method comprises the following steps that: (1) decoupling two coupling variables including time and space in a standard level set function in a dynamic model of which the structure is to be optimized, and meanwhile, expressing the level set function related to time as a matrix product form; (2) converting a partial differential equation of the time-related level set function into an ordinary differential equation so as to obtain a new linear system, and solving to obtain the time-related level set function; (3) carrying out finite element analysis on a macrostructure so as to calculate a target function and a constraint function of a structure optimization problem; and (4) calculating the sensitivity, which relates to a design variable of the target function and the constraint function obtained in the (3), and judging whether the target function is convergent or not after the design variable is updated. By use of the method, a discrete wavelet transform technology is adopted to carry out recompression on an interpolation matrix, efficiency is improved, and cost is lowered.
Owner:HUAZHONG UNIV OF SCI & TECH
Image splitting method based on level set relay
InactiveCN101504767AIncrease the level of automationAchieve segmentationImage analysisImage segmentationImage edge
The invention discloses a sequential level set-based method for automatically segmenting images, which comprises the steps: (1) inputting an image I to be segmented and automatically initializing a level set function in an image domain by using a morphological method; (2) evolving the level set function by using an iterative approach in a corresponding subdomain to obtain the level set function and a detected image border, and using the inside domain of the edge as a next subdomain; (3) converting an image edge detected in the subdomain into a binary image and storing the binary image; (4) judging whether the area of the next subdomain is zero, and executing a step (5) if the area of the next subdomain is zero, or returning to the step (1) if the area of the next subdomain is not zero; and (5) performing a 'combination' operation of the stored binary image, combining the image edges of all subdomains, and completing the image segmentation. The method has the advantages of detecting more image edges and automatically completing image segmentation, and can be used for segmenting natural images and medical images.
Owner:XIDIAN UNIV
Multi-scale structural material integrated design method based on shape features
ActiveCN107563010AImprove calculation accuracySmooth borderSpecial data processing applicationsMechanical modelsSoftware
The invention discloses a multi-scale structural material integrated design method based on shape features. The method is used for solving the technical problem that existing structural material integrated design methods are poor in practicability. According to the technical scheme, the shape features are used as basic elements of macro and micro design, a regular quadrangular finite element gridis adopted, and a structural shape is described by calculating a level set function of a feature structure; material properties of a microstructure are associated with macrostructure units through a homogenization method, and a multi-scale mechanical model based on a fixed grid is established; and shape position parameters of the shape features are selected to serve as design variables, and macroand micro topological optimization design is realized. Through the method, macrostructure design and microstructure design are associated, the level set method is adopted to describe the model, multiple microstructure forms can be obtained according to local conditions, an optimization result which has a smooth boundary and apparently contains feature information can be obtained, the method can beseamlessly integrated with existing computer-aided design software, and practicability is high.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Method and system for dividing up three-dimensional medical image of abdominal organ
InactiveCN102306373AQuality improvementEasy to analyzeImage enhancementImage segmentationVelocity function
The invention discloses a method and a system for dividing up a three-dimensional medical image of an abdominal organ. The method comprises the following steps of: preprocessing a medical sequence image of the abdominal organ; selecting a seed point from the preprocessed medical sequence image, and using a pixel point in a preset neighborhood range of the seed point as an initial division region of the abdominal organ; acquiring an edge calculation image of the preprocessed medical sequence image according to an edge stop function, and receiving a feebleness edge drawing instruction of a user to obtain an edge image of the abdominal organ by combining the feebleness edge drawing instruction with the edge calculation image; performing level set function evolution to update a velocity function by combining a level set velocity function with the edge image; and extracting the velocity function to obtain a target region. Therefore, according to the invention, the problem of fuzzy boundary in medical image division is solved by using a user interaction type input boundary fuzzy boundary, and the quality of the three-dimensional division image of the abdominal organ is improved.
Owner:SHENZHEN YORATAL DMIT
Covariance matching-based active contour tracking method
InactiveCN102063727AUniversalTracking results are accurateImage analysisAlgorithmBackground information
The invention relates to a covariance matching-based active contour tracking method and belongs to the technical field of visual tracking. In the covariance matching-based active contour tracking method, an image area energy term is modeled by using non-Euclidean geometry. The method comprises the following steps of: manually initializing a curve surrounding an objective and establishing a covariance matrix as a template of an objective contour for an area surrounded by the curve in a first frame; after the contour of the objective is obtained, recording a level set function value of the template to make preparation for a prior shape and calculating a symbolized distance function of the template; from the image of the next frame, deducing a gradient descent flow from a result of the previous frame according to the established energy functional and updating the level set function; and checking whether iteration stops or not. In the method, the tracking result is more accurate; meanwhile, the covariance matrix is used as an area descriptor and all kinds of information in an image sequence and the correlation between all kinds of information are considered comprehensively, and the method does not depend on foreground and background information distribution, so that the tracking method has universality.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
SAR (storage address register) image changing detection method based on improved C-V model
The invention discloses an SAR (storage address register) image changing detection method based on an improved C-V model, which mainly solves the problem that the precision of the detection result in the prior art is low. The implementation process of the method comprises the following steps of structuring a different map for two SAR images obtained in a same domain and in different time by a logarithmic ratio method; initializing a level set function as a symbol distance function, and dividing the different map area into two areas according to the negative and positive value of the level set function; respectively calculating gray average values of the two areas; structuring a total energy function including an energy function and a distance regular item based on the global regional information according to the gray level mean values of the twp areas and the level set function; and obtaining the minimum value of the total energy function through continuously updating the value of the level set function, and obtaining the change detection result map. According to the method provided by the invention, the level set function is used for showing a contour curve; as the value of the level set function is updated, the contour curve can be changed towards the boundary of the change area, thus, the global optimization and noise immunity can be realized; the precision of the detection result is improved, and the method can be used for disaster evaluation and environment detection.
Owner:XIDIAN UNIV
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