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- 摘要
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- 实验方案
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[IEEE 2018 41st International Conference on Telecommunications and Signal Processing (TSP) - Athens, Greece (2018.7.4-2018.7.6)] 2018 41st International Conference on Telecommunications and Signal Processing (TSP) - Improvement of Optic Disc Localization using Gabor Filters
摘要： The paper presents a supervised technique for the detection and localization of the optic disc (OD) in retinal images. The proposed processing technique is based on Discrete Fourier Transform (DFT) and Gabor filters (GFs). The algorithm of image patch processing and classification has two phases: the learning phase for the OD class definition and the testing phase for the patch processing and classification. Two features are used to check if a patch contains the OD: the magnitude and the phase values computed on the result of the convolution between the DFT of the patch and the bank of Gabor filters. Over 100 images from MESSIDOR database were tested and comparing with other similar works. The proposed algorithm gave better results in terms of accuracy of the OD localization for all types of OD.
关键词： Gabor filter,feature extraction,Discrete Fourier Transform,patch decomposition,optic disc localization
更新于2025-09-23 15:22:29
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Stroke diagnosis from retinal fundus images using multi texture analysis
摘要： Stroke is a cerebrovascular disease which is one of the significant causes of adult impairment. Research shows that retinal fundus images carry vital information for the prediction of various cardiovascular diseases like Stroke. This work investigates a multi-texture description for the computer aided diagnosis of Stroke from retinal fundus images. Texture of the retinal background is analyzed, thereby eliminating the need for segmentation. Gabor Filter (GF), Local Binary Pattern (LBP) and Histogram of Oriented gradients (HOG) are the texture descriptors implemented in this work. The texture descriptors are applied to the second Eigen channel obtained by Principal Component Analysis (PCA). Extracted features are concatenated to form a multi-texture representation and dimensionality reduction is done by ReliefF feature selection method. The compact feature vector is given to Na?ve Bayes classifier and performance metrics are evaluated. We have evaluated the performance of individual feature descriptors and multiple feature descriptors in retinal fundus images for stroke diagnosis. Multi-texture description outperforms individual texture descriptors by an accuracy of 95.1 %.
关键词： Gabor filter,ReliefF,histogram of oriented gradients,principal component analysis,local binary pattern,Stroke
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A New Registration Algorithm for Multimodal Remote Sensing Images
摘要： Automatic registration of remote sensing images is a challenging problem in the applications of remote sensing. The multimodal remote sensing images have significant nonlinear radiometric differences, which lead to the failure of area-based and feature-based registration methods. In this paper, to overcome significant nonlinear radiometric differences and large scale differences of multimodal remote sensing images, we propose a new registration algorithm, which can meet the need of initial registration of multimodal remote sensing images that conform to similarity transformation model. Our synthetic and real-data experimental results demonstrate the effectiveness and good performance of the proposed method in terms of visualization and registration accuracy.
关键词： multi-scale atlas,phase correlation,Log-Gabor filter,Multimodal remote sensing images,image registration
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Data Augmentation with Gabor Filter in Deep Convolutional Neural Networks for Sar Target Recognition
摘要： Deep Convolutional Neural Networks (DCNNs) have been widely used in target recognition due to the availability of large dataset. The DCNNs have the ability of learning highly hierarchical image feature, which provides great opportunity for synthetic aperture radar automatic target recognition (SAR-ATR). However, when the DCNNs were directly applied to the SAR target recognition, it will result in severe overfitting due to limited SAR image training data. To overcome this problem, we present a Gabor-Deep Convolutional Neural Networks (G-DCNNs). Instead of training a deep network with limited dataset of raw SAR images, Gabor features for multi-scale and multi-direction were used for data augmentation as training dataset at first. Then based on this data augmentation method, we designed a DCNNs for SAR image target recognition. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset prove the effectiveness of our method.
关键词： SAR,Gabor filter,DCNNs,data augmentation
更新于2025-09-23 15:21:21
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Machine learning-based mapping of micro-topographic earthquake-induced paleo Pulju moraines and liquefaction spreads from a digital elevation model acquired through laser scanning
摘要： The advent of public open source airborne laser scanning-produced digital elevation models (ALS DEM) has provided new perspectives on glacial geomorphology in the Nordic countries. Seismically-induced micro-topographic paleo-landforms can now be identified and mapped throughout the former Fennoscandian Ice Sheet, allowing spatial safety assessment for nuclear waste disposal. Automated machine learning techniques enable recognition of these fine-scale geomorphological features efficiently and in a consistent way nationwide. The current study focuses on automated recognition of paleo liquefaction spreads and Pulju moraines in northern Finland. Geomorphometric variables in different cell sizes were first derived from the 2 m ALS DEM by Gabor and principal curvature filtering to emphasize the elevational multi-scale texture of these paleo-seismic landforms. The Gabor textural variables were considered as a baseline method and the principal curvature features, including maximum and minimum curvature, were used because they have previously been proven critical in recognition of concave and convex elongated features. Both sets of raster variables were then turned into histogram-based features and input into a non-linear supervised multilayer perceptron early-stop committee which is a neural network classifier. The leave-one-out cross-validation performance results indicated principal curvature features to be highly successful with 94% accuracy. Principal curvatures provided a clear improvement to Gabor based features which provided significantly lower accuracies between 83?85%. The study demonstrates the high success of supervised neural network-based classification of ALS DEM data and derived textural features capturing the multi-scale nature of the micro-topographic liquefaction spreads and Pulju moraines. The approach could be utilized for time-efficient mapping of these paleo-seismic geomorphologies to complete paleo-seismic databases in formerly glaciated regions.
关键词： rotation invariant,histogram-based features,leave-one-out cross-validation,principal curvature,area invariant,multilayer perceptron,landforms,paleo-seismology,geomorphology,Gabor filter,Pulju moraine,liquefaction spreads
更新于2025-09-23 15:19:57
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Enhancement of thermographic images of composite laminates for debond detection: An approach based on Gabor filter and watershed
摘要： Spacecraft structures use materials which require high stiffness and low mass. Subjected to high thermal and acoustic loads, their health is of utmost importance. These structures are vulnerable to debonding and delaminations which are identified as defects. Non-destructive way of inspecting these components is very essential to detect the debonding defects. Debond defects are not visible to naked eyes and hence conventional optical cameras will not serve the purpose of automating inspection. For this purpose, we have used thermography. Passing the thermographic images through stages like enhancement, segmentation and feature extraction by using techniques like watershed segmentation, active contours and texture classification through Gabor filter are attempted in this study. Defects are brought out which help in taking corrective steps to avoid failure of the materials during actual life of the spacecraft.
关键词： Noise removal,Feature Extraction,Watershed algorithm,Active Contours,Gabor filter,Thermal Imaging
更新于2025-09-19 17:15:36
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[Lecture Notes in Computer Science] Pattern Recognition and Computer Vision Volume 11257 (First Chinese Conference, PRCV 2018, Guangzhou, China, November 23-26, 2018, Proceedings, Part II) || Deep Gabor Scattering Network for Image Classification
摘要： Deep learning models obtain exponential ascension in the field of image classification in recent years, and have become the most active research branch in AI research. The success of deep learning prompts us to make greater achievements in image classification. How to obtain effective feature representation becomes particularly important. In this paper, we combine the wavelet transformation and the idea of deep learning to build a new deep learning model, called Deep Gabor Scattering Network (DGSN). Concretely, in DGSN, we use the Gabor wavelet transformation to extract the invariant information of the images, partial least square regression (PLSR) for feature selection, and support vector machine (SVM) for classification. A key benefit of DGSN is that Gabor wavelet transformation can extract rich invariant features from the images. We show that DGSN is computationally simpler and delivers higher classification accuracy than related methods.
关键词： Invariant information,Gabor filter,Deep learning,Deep Gabor scattering network (DGSN)
更新于2025-09-10 09:29:36
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[IEEE 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Chongqing (2018.6.27-2018.6.29)] 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Fast Algorithm of Fingerprint Singularity Region Enhancement
摘要： In this paper, a fast fingerprint enhancement algorithm that can improve the singularity enhancement of fingerprint is proposed. It can overcome the problem that the Gabor filter can destroy the ridge structure near the fingerprint singularity point, and the directional Fourier filter can not repair the fingerprint line effect is not obviously. The new method (FS-Gabor) can quickly repair fingerprint lines while retaining the fingerprint structure in the vicinity of the singular points. The experimental results show that the EER of the fingerprint image filtered by the FS-Gabor method is lower than the method of directional Fourier filter and Gabor.
关键词： Gabor filter,directional Fourier filter,fingerprint enhancement,fingerprint singular point
更新于2025-09-10 09:29:36
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[IEEE 2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS) - Edinburgh, United Kingdom (2018.8.6-2018.8.9)] 2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS) - Competitive Coding Scheme based on 2D Log-Gabor filter for Palm Vein Recognition
摘要： This paper proposes a novel palm vein recognition method based on a competitive coding scheme using 2D log Gabor filtres. The proposed method consists of two major steps: (i) inspired by the bitwise competitive coding, the feature extraction employs 2D log Gabor filtering where the final feature map is composed by the winning codes of the lowest filters’ bank response, and (ii) the matching process uses the Jaccard distance as a metric to capture efficiently the similarities between the feature maps and allowing to make a decision. The experiments carried out on the challenging MS-PolyU database have shown that the proposed method yields a significant performance gains compared to existing state-of-the-art methods.
关键词： competitive coding,Multispectral biometrics,Palm vein recognition,feature extraction,log Gabor filter
更新于2025-09-10 09:29:36
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A New Image Quality Metric Using Compressive Sensing And A Filter Set Consisting of Derivative And Gabor Filters
摘要： This paper proposes an image quality metric (IQM) using compressive sensing (CS) and a filter set consisting of derivative and Gabor filters. In this paper, compressive sensing that is used for acquiring a sparse or compressible signal with a small number of measurements is used for measuring the quality between the reference and distorted images. However, an image is generally neither sparse nor compressible, so a CS technique cannot be directly used for image quality assessment. Thus, for converting an image into a sparse or compressible signal, the image is convolved with filters such as the gradient, Laplacian of Gaussian, and Gabor filters, since the filter outputs are generally compressible. A small number of measurements obtained by a CS technique are used for evaluating the image quality. Experimental results with various test images show the effectiveness of the proposed algorithm in terms of the Pearson correlation coefficient (CC), root mean squared error, Spearman rank order CC, and Kendall CC.
关键词： Difference Mean Opinion Score,Gabor Filter,Image Quality Assessment,Compressive Sensing,Derivative Filters
更新于2025-09-10 09:29:36