- 标题
- 摘要
- 关键词
- 实验方案
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An Image Segmentation Method Based on Improved Regularized Level Set Model
摘要： When the level set algorithm is used to segment an image, the level set function must be initialized periodically to ensure that it remains a signed distance function (SDF). To avoid this defect, an improved regularized level set method-based image segmentation approach is presented. First, a new potential function is defined and introduced to reconstruct a new distance regularization term to solve this issue of periodically initializing the level set function. Second, by combining the distance regularization term with the internal and external energy terms, a new energy functional is developed. Then, the process of the new energy functional evolution is derived by using the calculus of variations and the steepest descent approach, and a partial differential equation is designed. Finally, an improved regularized level set-based image segmentation (IRLS-IS) method is proposed. Numerical experimental results demonstrate that the IRLS-IS method is not only effective and robust to segment noise and intensity-inhomogeneous images but can also analyze complex medical images well.
关键词： image segmentation,energy functional,level set,distance regularization term
更新于2025-09-23 15:23:52
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Hyperspectral band selection for soybean classification based on information measure in FRS theory
摘要： Soybeans and soy foods have attracted widespread attention due to their health benefits. Special varieties of soybeans are in demand from soybean processing enterprises. Because of the advantage of rapid measurement with minimal sample preparation, hyperspectral imaging technology is used for classifying soybean varieties. Based on fuzzy rough set (FRS) theory, the research of hyperspectral band selection can provide the foundation for variety classification. The performance of band selection with Gaussian membership functions and triangular membership functions under various parameters were explored. Appropriate ranges of parameters were determined by the number of bands and mutual information of subsets relative to the decision. The effectiveness of the proposed algorithms was validated through experiments on soybean hyperspectral datasets by building two classification methods, namely Extreme Learning Machine and Random Forest. Compared with ranking methods, the proposed algorithm provides a promising improvement in classification accuracy by selecting highly informative bands. To further reduce the size of the subset, a post-pruning design was used. For the Gaussian membership function, a subset containing eight bands achieved an average accuracy of 99.11% after post-pruning. As well as classification accuracy, we explored stability of band selection algorithm under small perturbations. The band selection algorithm of the Gaussian membership function was more stable than that of the triangular membership function. The results showed that the information measure (IM) based band selection algorithm is effective at obtaining satisfactory classification accuracy and providing stable results under perturbations.
关键词： Soybean classification,Information measure,Band selection,Fuzzy rough set,Hyperspectral imaging
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE Industry Applications Society Annual Meeting (IAS) - Portland, OR, USA (2018.9.23-2018.9.27)] 2018 IEEE Industry Applications Society Annual Meeting (IAS) - A Solar PV, BES, Grid and DG Set Based Hybrid Charging Station for Uninterruptible Charging at Minimized Charging Cost
摘要： In this paper, a charging station (CS) is proposed that uses a solar photovoltaic (PV) array, a battery energy storage system (BES), the grid and a diesel generator (DG) set to provide uninterruptible charging of electric vehicles (EVs). However, these energy sources are utilized in a way that minimizes the operational cost of the CS. Therefore, it reduces the charging cost of the electric vehicles (EVs). To achieve uninterruptible charging and to minimize the charging cost, a charging strategy is proposed that prioritizes the use of energy sources. Based on this, the solar PV and BES energy are used as a priority. After that, the grid is used, and finally, a DG set is used when all energy sources are not accessible. This strategy is based on the cost of electricity per kWh. Normally, the rooftop solar PV array offers power at INR 4.5-5/kWh. The grid offers power at INR 10/kWh, and DG set offers at INR 17-20/kWh. To further minimize the charging cost, the single phase two winding self-excited induction generator (SEIG) based DG set is operated at the single point of saturation characteristic to generate much high power than its rated power. Moreover, a single two-leg voltage source converter (VSC) does multiple tasks such as, 1) generation of sinusoidal voltage in standalone mode, 2) regulation of generator voltage and frequency, 3) management of power flow, 4) reactive power compensation and harmonics current elimination and it also reduces the initial cost of the CS. To obtain ceaseless charging while connecting the grid/DG set to the CS, the point of common coupling (PCC) voltage is synchronized with the grid/DG set voltage. The CS provides both AC and DC output ports for charging the EVs. To charge the EVs on AC port, the CS uses solar PV array and BES energy to generate a sinusoidal voltage of 220V and 50Hz. Moreover, with both grid and DG, the CS draws power at unity power factor (PF) with current total harmonics distortion (THD) less than 5% as required by an IEEE 519 standard.
关键词： Solar PV Generation,EV Charging Station,Power Quality,Uninterruptible Power,DG Set
更新于2025-09-23 15:23:52
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A methodology for topology optimization based on level set method and its application to piezoelectric energy harvester design
摘要： Compared to a density based procedure, the level set method can acquire a clear boundary without any intermediate density elements, and has become a topical issue in topology optimization studies. In this method, the material properties of the discretized elements are usually defined as the design variables, giving rise to the so called discrete or sawtooth topologies. In this paper, a topology optimization methodology based on level-set method (LSM) and radial basis function (RBF) is proposed. To enhance the performance of the LSM, an improved material interpolation model is proposed. The RBF based post-processor is proposed to smooth the preliminary optimized topology. The proposed method is applied to the topology design of a piezoelectric energy harvester. The effect of different penalization factors is compared and analyzed. The numerical results validate the feasibility and effectiveness of the proposed method.
关键词： Coupled problems,topology optimization,level set method
更新于2025-09-23 15:22:29
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[IEEE 2018 3rd International Conference for Convergence in Technology (I2CT) - Pune (2018.4.6-2018.4.8)] 2018 3rd International Conference for Convergence in Technology (I2CT) - Modified Level-Set for Segmenting Breast Tumor from Thermal Images
摘要： Contactless, painless and radiation-free thermal imaging technique is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer aided diagnosis of breast cancer. This work uses a modified version of level-set called marker-controlled level-set for segmentation along with pre-processing. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: a) marker-controlled Level-set segmentation of anisotropic diffusion filtered preprocessed image versus b) Segmentation using marker-controlled level-set on a Gaussian-filtered image. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer aided diagnosis of breast cancer.
关键词： Breast,Thermograms,Gaussian,Anisotropic diffusion,Segment,Level set
更新于2025-09-23 15:22:29
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A Review of Point Feature Based Medical Image Registration
摘要： Point features, as the basis of lines, surfaces, and bodies, are commonly used in medical image registration. To obtain an elegant spatial transformation of extracted feature points, many point set matching algorithms (PMs) have been developed to match two point sets by optimizing multifarious distance functions. There are ample reviews related to medical image registration and PMs which summarize their basic principles and main algorithms separately. However, to data, detailed summary of PMs used in medical image registration in different clinical environments has not been published. In this paper, we provide a comprehensive review of the existing key techniques of the PMs applied to medical image registration according to the basic principles and clinical applications. As the core technique of the PMs, geometric transformation models are elaborated in this paper, demonstrating the mechanism of point set registration. We also focus on the clinical applications of the PMs and propose a practical classification method according to their applications in different clinical surgeries. The aim of this paper is to provide a summary of point-feature-based methods used in medical image registration and to guide doctors or researchers interested in this field to choose appropriate techniques in their research.
关键词： Assessment,Application,Point set matching,Medical image registration,Optimization
更新于2025-09-23 15:22:29
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Sketchpointnet: A Compact Network for Robust Sketch Recognition
摘要： Sketch recognition is a challenging image processing task. In this paper, we propose a novel point-based network with a compact architecture, named SketchPointNet, for robust sketch recognition. Sketch features are hierarchically learned from three miniPointNets, by successively sampling and grouping 2D points in a bottom-up fashion. SketchPointNet exploits both temporal and spatial context in strokes during point sampling and grouping. By directly consuming the sparse points, SketchPointNet is very compact and efficient. Compared with state-of-the-art techniques, SketchPointNet achieves comparable performance on the challenging TU-Berlin dataset while it significantly reduces the network size.
关键词： point set,stroke pattern,Sketch recognition,deep neural network
更新于2025-09-23 15:22:29
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Automatic optic disc localization and segmentation in retinal images by a line operator and level sets
摘要： BACKGROUND: Existing methods may fail to locate and segment the optic disc (OD) due to imprecise boundaries, inconsistent image contrast and deceptive edge features in retinal images. OBJECTIVE: To locate the OD and detect the OD boundary accurately. METHODS: The method exploits a multi-stage strategy in the detection procedure. Firstly, OD location candidate regions are identi?ed based on high-intensity feature and vessels convergence property. Secondly, a line operator ?lter for circular brightness feature detection is designed to locate the OD accurately on candidates. Thirdly, an initialized contour is obtained by iterative thresholding and ellipse ?tting based on the detected OD position. Finally, a region-based active contour model in a variational level set formulation and ellipse ?tting are employed to estimate the OD boundary. RESULTS: The proposed methodology achieves an accuracy of 98.67% for OD identi?cation and a mean distance to the closest point of 2 pixels in detecting the OD boundary. CONCLUSION: The results illuminate that the proposed method is effective in the fast, automatic, and accurate localization and boundary detection of the OD. The present work contributes to the more effective evaluation of the OD and realizing automatic screening system for early eye diseases to a large extent.
关键词： optic disc segmentation,level set method,retinal images,Optic disc localization
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Main Aortic Segmentation from CTA with Deep Feature Aggregation Network
摘要： In this study, we propose a Deep Feature Aggregation network (DFA-Net) for main aortic segmentation from CTA(Computed Tomography Angiography) by aggregating features from forwarding layers to leverage more visual information. To practically verify the effectiveness of our method, we collect 90 CTA volumes from Beijing AnZhen Hospital up to over 60 thousands 2-D slices. First, we use a level-set based algorithm to efficiently generate the dataset for training and validating the deep model. Then the dataset is divided into three parts, 70 instances are used for training and 5 instances are used for validating the best parameters, and the rest 15 instances are used for testing the generalization of the model. Finally, the testing result shows that mIoU(mean Intersection-over-Union) of the segmentation result is 0.943, which indicates that by properly aggregating more visual features in a deep network the segmentation model can achieve state-of-the-art performance.
关键词： CTA,feature aggregation,level set,main aortic segmentation
更新于2025-09-23 15:22:29
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Multi-fidelity EM simulations and constrained surrogate modelling for low-cost multi-objective design optimisation of antennas
摘要： In this study, a technique for low-cost multi-objective design optimisation of antenna structures has been proposed. The proposed approach is an enhancement of a recently reported surrogate-assisted technique exploiting variable-fidelity electromagnetic (EM) simulations and auxiliary kriging interpolation surrogate, the latter utilised to produce the initial approximation of the Pareto set. A bottleneck of the procedure for higher-dimensional design spaces is a large number of training data samples necessary to construct the surrogate. Here, the authors propose a procedure that allows us to confine the model domain to the subset spanned by the reference points, including the extreme Pareto-optimal designs obtained by optimising the individual objectives as well as an additional design that determines the Pareto front curvature. Setting up the surrogate in the constrained domain leads to a dramatic reduction of the required number of data samples, which results in lowering the overall cost of the optimisation process. Furthermore, the model domain confinement is generic, i.e. applicable for any number of design goals considered. The proposed technique is demonstrated using an ultra-wideband monopole antenna optimised with respect to three objectives. Significant reduction of the design cost is obtained as compared to the reference surrogate-assisted algorithm.
关键词： Pareto set,antenna structures,variable-fidelity EM simulations,kriging interpolation surrogate,multi-objective design optimisation,ultra-wideband monopole antenna
更新于2025-09-23 15:21:21