- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
[IEEE 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) - Shah Alam, Malaysia (2018.7.11-2018.7.12)] 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) - An Effective Enhancement and Segmentation of Coronary Arteries in 2D Angiograms
摘要： Vessel enhancement in two-dimensional angiogram images is an essential pre-requisite step towards the isolation of coronary arteries. Hessian-based filters are the most commonly used vessel enhancement filters; however, these filters are more sensitive to noise and suppress the bifurcation regions. Suppression of bifurcation regions results in disconnected vessels. In this study, we present a technique that enhances the arteries of the heart in 2D angiograms and also refines the noisy vesselness obtained through Frangi’s method by using guided filter which produces more enhanced image that can be used as an effective pre-processing step for binarization of the Frangi vessel response having less discontinuities and joint suppression. The proposed approach makes use of the guided filter which smooths the edges, and at the same time preserves the edges as well for the enhancement of vessels. Following this filter, an Adaptive thresholding is applied to segment the coronary arteries from the angiogram. The proposed method has been tested on real angiography images and the efficiency of the method has been shown qualitatively as well as quantitatively.
关键词： adaptive thresholding,guided filter,segmentation,vessel enhancement,coronary arteries
更新于2025-09-09 09:28:46
-
Possibilistic Clustering Algorithm Incorporating Grey-Level Histogram and Spatial Information for Image Segmentation
摘要： Image segmentation is a process of segmenting an image into non-intersecting regions containing homogeneous pixels that are inhomogeneous with those in other adjacent regions. In this paper, a possibilistic clustering algorithm incorporating grey-level histogram and spatial information (PCA_HS) for image segmentation is proposed. The grey-level histogram speeds up the algorithm and the spatial information enhances its robustness to noise and outliers. To assess the proposed algorithm, four widely used validity indexes are computed and discussed. As the experimental quantitative and qualitative results on real images with and without noise show, PCA_HS can preserve the homogeneity and integrality of the regions and hence is more effective and efficient than traditional PCA.
关键词： grey-level histogram,Image segmentation,possibilistic clustering,spatial information
更新于2025-09-09 09:28:46
-
Perceptual hashing for SAR image segmentation
摘要： Image segmentation is an important step in the implementation of the interpretation of synthetic aperture radar (SAR) image due to speckle. This article proposes a SAR image segmentation method based on perceptual hashing. The new algorithm is divided into two phases. The first phase is to obtain initial regions with multi-thresholding based on histogram after reducing the speckle noise. The initial regions are used as input data. And the next phase is to merge regions according to the similarity between regions. In this phase, to segment SAR image effectively, the proposed hashing algorithm is used to obtain hash value and similarity between regions, which preserve the texture features of SAR images. In addition, we can obtain a smooth segmentation result by reducing the redundant information with principal component analysis. Furthermore, morphological methods are used to eliminate the uneven background in the segmentation results. These improvements make our algorithm more effective to segment the images with high speed. The experimental results of four real and one synthetic SAR images verify the efficiency of our algorithm.
关键词： multi-thresholding,perceptual hashing,region merging,principal component analysis,SAR image segmentation
更新于2025-09-09 09:28:46
-
Segmentation and Classification of Optic Disc in Retinal Images
摘要： Image segmentation plays a vital role in image analysis for diagnosis of various retinopathy diseases. For the detection of glaucoma and diabetic retinopathy, manual examination of the optic disc is the standard clinical procedure. The proposed method makes use of the circular transform to automatically locate and extract the Optic Disc (OD) from the retinal fundus images. The circular transform operates with radial line operator which uses the multiple radial line segments on every pixel of the image. The maximum variation pixels along each radial line segments are taken to detect and segment OD. The input retinal images are preprocessed before applying circular transform. The optic disc diameter and the distance from optic disc to macula are found for a sample of 20 images. An Extreme Learning Machine classifier is used to train the neural network to classify the images as normal or abnormal. Its performance is compared with Support Vector Machine in terms of computation time and accuracy. It is found that computation time is less than 0.1 sec and accuracy is 97.14% for Extreme Learning Machine classifier.
关键词： extreme learning machine,Circular transform,optic disc,segmentation,macula
更新于2025-09-09 09:28:46
-
A Multi-Resolution Blending Considering Changed Regions for Orthoimage Mosaicking
摘要： Blending processing based on seamlines in image mosaicking is a procedure designed to obtain a smooth transition between images along seamlines and make seams invisible in the final mosaic. However, for high-resolution aerial orthoimages in urban areas, factors such as projection differences, moving objects, and radiometric differences in overlapping areas may result in ghosting and artifacts or visible shifts in the final mosaic. Such a mosaic is not a true reflection of the earth’s surface and may have a negative impact on image interpretation. Therefore, this paper presents a multi-resolution blending method considering changed regions to improve mosaic image quality. The method utilizes the region change rate (RCR) to distinguish changed regions from unchanged regions in overlapping areas. The RCR of each region is computed using image segmentation and change detection methods. Then, a mask image is generated considering changed regions, and Gaussian and Laplacian pyramids are constructed. Finally, a multi-resolution reconstruction is performed to obtain the final mosaic. Experimental results from digital aerial orthoimages in urban areas are provided to verify this method for blending processing based on seamlines in mosaicking. Comparisons with other methods further demonstrate the potential of the presented method, as shown in a detailed comparison in three typical cases of the seamline passing by buildings, the seamline passing through buildings, and the seamline passing through areas with large radiometric differences.
关键词： mosaic,blending,segmentation,multi-resolution,change detection
更新于2025-09-09 09:28:46
-
[IEEE 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom) - Ostrava (2018.9.17-2018.9.20)] 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom) - Supervised Level Sets For Dermoscopic Image Segmentation
摘要： In this paper, we propose a novel segmentation method that has been used for segmenting lesions in dermoscopy images. This method uses the variational level sets formulation with a novel area term based on supervised learning that results in the global optimization of a cost function, that can potentially result in a robust segmentation of the images. This term uses a mixture of Gaussians that are trained from a set of training images, and evolves an active contour such that the difference between the learned models and the empirical distributions obtained from the evolving curve for both the lesion and the skin are minimized. In the end, our approach is validated on the publicly available PH2 dermoscopy imaging dataset and the results show that the proposed method outperforms the other state-of-the-art methods that have been considered in this paper.
关键词： Gaussian mixture models,Variational level sets,Segmentation,Skin cancer,Dermoscopy
更新于2025-09-09 09:28:46
-
[IEEE 2018 15th European Radar Conference (EuRAD) - Madrid, Spain (2018.9.26-2018.9.28)] 2018 15th European Radar Conference (EuRAD) - A Stand Alone Millimetre Wave Imaging Scanner: System Design and Image Analysis Setup
摘要： Millimetre wave sensors are capable of measuring the structure and composition as well as detecting small variations thereof in a wide range of dielectric materials, such as plastics, dry goods and foodstuffs. To produce an image that modern image recognition algorithms can be applied on, a resolution, i.e. pixel density, comparable to those of optical cameras has to be realized. In this paper, we present a rotating scanner system that operates in a CW mode at 90 GHz and allows for a high pixel density for medium measurement object velocities using only a single measurement channel. Additionally, we present an image exploitation setup for the detection of defects in scanned goods and the fusion of amplitude and phase data as well as images acquired from an optical camera for fast and easy goods inspection.
关键词： image matching,object segmentation,microwave imaging,manufacturing industries,radar imaging,image recognition,millimeter wave radar,product safety,image fusion
更新于2025-09-09 09:28:46
-
[IEEE 2018 24th International Conference on Pattern Recognition (ICPR) - Beijing, China (2018.8.20-2018.8.24)] 2018 24th International Conference on Pattern Recognition (ICPR) - A New Foreground Segmentation Method for Video Analysis in Different Color Spaces
摘要： A new foreground segmentation method is presented in this paper for video analysis. Specifically, a new feature representation scheme is first proposed in different color spaces, namely, the RGB, the YIQ, and the YCbCr color spaces. The new feature vector, which integrates the color values in a particular color space, the horizontal and vertical Haar wavelet features, and the temporal difference features, enhances the discriminatory power. A new Global Foreground Modeling (GFM) method is then presented to improve upon the popular video analysis approaches. The Bayes classifier is finally applied for foreground segmentation in video. Experimental results using the New Jersey Department of Transportation (NJDOT) traffic video sequences show that the new foreground segmentation method achieves better performance than the popular video analysis methods.
关键词： Global Foreground Modeling,video analysis,Haar wavelet features,Bayes classifier,temporal difference features,foreground segmentation,color spaces
更新于2025-09-09 09:28:46
-
12.2: A 3D Display Parallel System: Light Field Re-rendering and Depth Sense Optimization
摘要： The main benefit of 3D display over 2D display is the obvious ability to create a more lifelike character with high depth sense. However, the limitation of human eye’s visual mechanism, unartful 3D scene structure design, or bad viewing condition always emerges poor depth perception experience or even physiological discomfort during the watching time, which is often sub-optimal for mass high-quality 3D display productions. To solve this problem, we propose a novel 3D display parallel system for depth sense optimization and it empirically guides how the light field should be re-rendered. Structurally, the parallel system consists of an artificial perception measurement system, a display evaluation model and a light field display rendering system, which includes the display calibration, scene capture, light field data processing and display. Particularly, the system can systematically analyze and model various factors affecting the depth sense which learned through the measurement system, like scene structure, objects’ speeds in 3D video and so on. And those sense factors can be personally modified or increased according to the viewer’s demands or technical improvement. Moreover, the light field could be real-time re-rendered, based on some image processing technology, optical flow analysis and object segmentation (or tracking) (especially the one-shot video segmentation). Theory and algorithms are developed and experimental validation results show a superior performance.
关键词： Light Field Re-rendering,Depth Sense,3D Video Processing,One-shot Segmentation,3D Display Parallel System
更新于2025-09-09 09:28:46
-
[Smart Innovation, Systems and Technologies] Smart Intelligent Computing and Applications Volume 105 (Proceedings of the Second International Conference on SCI 2018, Volume 2) || Dimensionality Reduction Using Subset Selection Method in Framework for Hyperspectral Image Segmentation
摘要： This paper presents a dimensionality reduction method using subset selection for hyperspectral image segmentation framework. This framework consists of three stages—dimensionality reduction, hierarchical image fusion, and segmentation. A methodology based on subset construction is used for selecting k informative bands from d bands dataset. In this selection, similarity metrics such as Average Pixel Intensity (API), Histogram Similarity (HS), Mutual Information (MI) and Correlation Similarity (CS) are used to create k distinct subsets and from each subset, a single band is selected. Hierarchical fusion is used to create a single high quality image. After getting fused image, Fuzzy c-means (FCM) algorithm is used for segmentation of image. The qualitative and quantitative analysis shows that CS similarity metric in dimensionality reduction algorithm gets high-quality segmented image.
关键词： subset selection,hierarchical image fusion,hyperspectral image segmentation,dimensionality reduction,Fuzzy c-means (FCM)
更新于2025-09-09 09:28:46