检索结果-内蒙古大学图书馆

Nonlinear Gaussian filtering approach for object segmentation

IEE PROCEEDINGS-vision image AND SIGNAL processing 1999年第3期146卷 137-143页

作者： Izquierdo, E Ghanbari, M Univ Essex Dept Elect Syst Engn Colchester CO4 3SQ Essex England

Gaussian filter kernels can be used to smooth textures for image segmentation. In so-called anisotropic diffusion techniques, the smoothing process is adapted according to the edge direction to preserve the edges. However, the segment borders obtained with this approach do not necessarily coincide with physical object contours, especially in the case of textured objects. A novel segmentation technique involving weighted Gaussian filtering is introduced. The extraction of true object masks is performed by smoothing edges due to texture and preserving true object borders. In this process, additional features such as disparity or motion are taken into account. The method presented has been successfully applied in the context of object segmentation to natural scenes and object-based disparity estimation for stereoscopic applications.

关键词： motion adaptive filters adaptive signal processing Gaussian filter kernels object-based disparity estimation segment borders feature extraction image segmentation Gaussian processes anisotropic diffusion techniques edge direction object segmentation computer vision and image processing techniques Filtering methods in signal processing stereo image processing image texture smoothing edge detection object masks extraction natural scenes image texture image recognition nonlinear filters physical object contours stereoscopic applications nonlinear Gaussian filtering adaptive smoothing smoothing methods weighted Gaussian filtering

来源：评论

学校读者我要写书评

暂无评论

Cooperative simultaneous localisation and mapping using independent Rao-Blackwellised filters

引用

IET computer vision 2012年第5期6卷 407-414页

作者： Arturo, G. A. Monica, B. G. Miguel, J. C. Oscar, R. G. David, U. G. Univ Miguel Hernandez Elche Elche Spain

This study focuses on an approach to the multi-robot simultaneous localisation and mapping (SLAM) problem. The authors consider that a team of robots start the map building process from known initial poses and move through the environment observing a set of landmarks. In particular, the authors consider that the robots are equipped with vision sensors and are capable to compute the relative distance to natural visual landmarks. In the proposed approach, each robot computes an own global map and integrates its own observations in it. In addition, each robot is also capable of integrating the measurements obtained by other robots in his own map, thus cooperating to compute a global map using the information provided by all the robots in the team. In this way, each robot in the team builds a different global map. The approach presented here differs from others in the sense that each robot maintains an independent SLAM filter, and still each robot can introduce the observations of other robots in his own map. The authors present a set of experimental results obtained in a simulated environment that validate the proposed approach.

关键词： multirobot simultaneous localisation and mapping problem multi-robot systems filtering theory natural visual landmark computer vision and image processing techniques mobile robots robot vision SLAM (robots) global map independent SLAM filter map building process Optical, image and video signal processing cooperative simultaneous localisation and mapping Mobile robots independent Rao-Blackwellised filter Filtering methods in signal processing vision sensor

来源：评论

学校读者我要写书评

暂无评论

Analysis on segmentation and biomarker-based approaches for liver cancer detection: A survey

引用

IET image processing 2021年第4期15卷 845-855页

作者： Gunasekhar, P. Vijayalakshmi, S. RMK Engn Coll Kavataipettai 601206 Tamil Nadu India

Liver cancer is the major reason for death in this entire world. Manual detection of cancer tissue is found time consuming and difficult. Therefore, the development of an automatic detection approach with high accuracy for liver cancer is considered as the main aim of this work. The image processing approach can use the CAD for the classification of liver cancer in order to assist the physician in the decision-making process. An automated approach to effective classification of the liver tumour using effective features is conveyed in terms of the CAD system. Traditionally, radiologists delineate the liver and liver lesion on a slice-by-slice basis, which is time consuming and susceptible to inter- and intra-rater variations. Automatic methods for the segmentation of liver and liver tumours are, thus, highly demanded in clinical practice. A systematic review is being carried out to detect reported liver cancer from 2013 to 2020. Finally, a more precise technical direction is provided for all researchers in this review. Research gaps for earlier detection and its potential future aspects are also discussed.

关键词： Optical, image and video signal processing Biomedical measurement and imaging computer vision and image processing techniques Patient diagnostic methods and instrumentation Biology and medical computing

来源：评论

学校读者我要写书评

暂无评论

Underwater image restoration: A state-of-the-art review

引用

IET image processing 2021年第2期15卷 269-285页

作者： Fayaz, Sheezan Parah, Shabir A. Qureshi, G. J. Kumar, Vijaya Univ Kashmir Dept Elect & Instrumentat Technol Srinagar India Govt Jammu & Kashmir Higher Educ Dept Jammu Jammu & Kashmir India Univ New South Wales Sch Comp Sci & Engn Sydney NSW Wales

Underwater imaging is one of the hot areas of research and is receiving considerable attention from the research community due to the challenges involved. Underwater images are prone to various distortions like poor contrast and colour deviation. Light scattering and light absorption in water medium are the main reasons for degradation in subaquatic images. Scattering of visible-light energy reduces the sharpness of image whereas varying degrees of light attenuation travelling in water results in the colour change. Restoration of distorted underwater images is an ill-posed and challenging problem. Various techniques and methodologies are being used to process and restore underwater images. In this study, we present a state-of-the-art review of various conventional and computer vision-based algorithms and techniques, developed so far, to present a clearer view of the methods used for underwater image restoration. We discuss various conditions for which the schemes have been developed as well as highlight the quality assessment methods used to evaluate their performance. We compare various state-of-art schemes based on various subjective and objective indices and discuss future research directions in the field of underwater image restoration.

关键词： Optical, image and video signal processing computer vision and image processing techniques Computing in other engineering fields

来源：评论

学校读者我要写书评

暂无评论

A generalized quality assessment method for natural and screen content images

引用

IET image processing 2021年第1期15卷 166-179页

作者： Loh, Woei-Tan Bong, David B. L. Univ Malaysia Sarawak Dept Elect & Elect Kota Samarahan Malaysia

A generalized objective quality assessment method is proposed for natural images and screen content images. Since natural images and screen content images have different statistical properties, the modelling of a generalized quality assessment method that works for both types of images is complicated because some properties of natural images and screen content images are conflicting to one another. The proposed method assesses the perceptual quality of an image based on edge magnitude and direction. In this method, an image is first separated into regions with high and low gradients. Gradient is used due to the small perceptual span of the human visual system for textual content. For high gradient regions, small kernel size of Prewitt operators is used to obtain the gradient magnitude and direction. Correspondingly, bigger kernel size of Prewitt operators is utilized for low gradient regions. Visual quality indices are computed from both regions and pooled to obtain the final quality index. From the performance comparison, it is shown that the proposed method could assess the perceived quality of natural images and screen content images with high accuracy.

关键词： image recognition Interpolation and function approximation (numerical analysis) computer vision and image processing techniques Other topics in statistics Interpolation and function approximation (numerical analysis) Other topics in statistics

来源：评论

学校读者我要写书评

暂无评论

Candidate box fusion based approach to adjust position of the candidate box for object detection

引用

IET image processing 2021年第12期15卷 2799-2809页

作者： Cao, Jie Ren, Wei Zhang, Hong Chen, Zuohan Lanzhou Univ Technol Sch Comp & Commun Lanzhou 730050 Peoples R China Lanzhou Univ Technol Sch Elect & Informat Engn Lanzhou 730050 Peoples R China Engn Res Ctr Urban Railway Transportat Gansu Prov Urban Railway Transportat Lanzhou 730050 Peoples R China

The method of object detection has been applied to all aspects in our lives. Although object detection methods based on deep learning have been widely used in various fields, there are still some overlooked problems in the candidate box selection stage. The detection results of traditional candidate box selection methods can only select a relatively optimal maximum candidate box. If the maximum candidate box is still not accurate enough, this type of methods will not be able to do adjust it. To solve this problem, an object detection method based on the multiple candidate box fusion is proposed. The method can not only retain the maximum candidate box and delete the non-maximum candidate box, but also adjust the position of the maximum candidate box again. Thereby a more accurate maximum candidate box can be obtained. In order to verify the generalization ability of the method, the candidate box fusion method is combined with the two object detection frameworks: faster R-CNN model and YOLOv3 model. The results of these experiments prove that the proposed method can achieve higher detection accuracy and complete the object detection task more effectively.

关键词： Optical, image and video signal processing computer vision and image processing techniques Machine learning (artificial intelligence)

来源：评论

学校读者我要写书评

暂无评论

Homography-based ground plane detection using a single on-board camera

引用

IET INTELLIGENT TRANSPORT SYSTEMS 2010年第2期4卷 149-160页

作者： Arrospide, J. Salgado, L. Nieto, M. Mohedano, R. Univ Politecn Madrid Grp Tratamiento Imagenes ETS Ing Telecomunicac Madrid Spain

This study presents a robust method for ground plane detection in vision-based systems with a non-stationary camera. The proposed method is based on the reliable estimation of the homography between ground planes in successive images. This homography is computed using a feature matching approach, which in contrast to classical approaches to on-board motion estimation does not require explicit ego-motion calculation. As opposed to it, a novel homography calculation method based on a linear estimation framework is presented. This framework provides predictions of the ground plane transformation matrix that are dynamically updated with new measurements. The method is specially suited for challenging environments, in particular traffic scenarios, in which the information is scarce and the homography computed from the images is usually inaccurate or erroneous. The proposed estimation framework is able to remove erroneous measurements and to correct those that are inaccurate, hence producing a reliable homography estimate at each instant. It is based on the evaluation of the difference between the predicted and the observed transformations, measured according to the spectral norm of the associated matrix of differences. Moreover, an example is provided on how to use the information extracted from ground plane estimation to achieve object detection and tracking. The method has been successfully demonstrated for the detection of moving vehicles in traffic environments.

关键词： ground plane transformation matrix erroneous measurement removal computer vision and image processing techniques nonstationary camera traffic environments feature matching approach linear estimation framework onboard motion estimation motion estimation Optical, image and video signal processing single onboard camera object tracking image matching homography calculation method object detection moving vehicles detection image sensors ego-motion calculation cameras ground plane estimation homography-based ground plane detection

来源：评论

学校读者我要写书评

暂无评论

A hybrid BPSO-SVM for feature selection and classification of ocular health

引用

IET image processing 2021年第2期15卷 542-555页

作者： Keerthiveena, B. Esakkirajan, S. Subudhi, Badri Narayan Veerakumar, T. PSG Coll Technol Dept Instrumentat & Control Syst Engn Coimbatore 641004 Tamil Nadu India Indian Inst Technol Jammu Dept Elect Engn Jammu *** Jammu & Kashmir India Natl Inst Technol Goa Dept Elect & Commun Engn Veling 403401 Goa India

Glaucoma and diabetic retinopathy are the most common eye diseases and the leading cause of blindness around the world. The prime objective of this study is to devise and develop an experimental computer-aided diagnosis system to provide an efficient way for assisting the ophthalmologist in early detection of ocular diseases such as glaucoma and diabetic retinopathy. The proposed technique follows three stages: Pre-processing, feature selection and classification. Initially, the fundus image is pre-processed to extract the green channel image, and the obtained green channel image is further enhanced using contrast limited adaptive histogram equalisation technique. Three different kinds of features: Clinical features, transform domain features and structural features are utilised to extract the relevant information from the enhanced fundus images. To avoid redundant information, an improved feature selection mechanism is used to select the optimum set of features from the extracted features. Subsequently, the selected features are used to train the support vector machine classifier for the classification of the retinal diseases with 10-fold cross-validation. The performance of the proposed method is assessed using eight different quantitative evaluation measures. The experimental results demonstrate the effectiveness of the proposed work over prior works for the early detection of ocular diseases.

关键词： Optical, image and video signal processing Biomedical measurement and imaging computer vision and image processing techniques Optical and laser radiation (medical uses) Patient diagnostic methods and instrumentation Biology and medical computing

来源：评论

学校读者我要写书评

暂无评论

Detection and localisation of magnetic objects

引用

IET SCIENCE MEASUREMENT & TECHNOLOGY 2007年第5期1卷 245-254页

作者： Barrell, Y. Naus, H. W. L. TNO Def Security & Safety NL-2509 JG The Hague Netherlands

Detection and localisation of hidden magnetic objects is studied. The concomitant disturbance of the earth magnetic field is exploited. Magnetic fields and or gradients are measured with a number of sensors. Two point models for magnetic fields are selected for the analysis: the magnetic dipole and its quadrupole extension. It is shown how to apply least squares analysis of the data in order to detect and localise magnetised objects. The theoretical framework is tested in simulations, including noise. Two methods to do the minimisation are chosen. The formalism performs well in the simulations. Detection and localisation of the model objects is successful. No decisive differences in performance of the two minimisation methods are found. Results for the position parameters are reliable in any case. We have evaluated the goodness of fit in our simulations. Theoretical and simulated chi-square distributions are compared for different fit models and noise distributions with satisfactory results. The obtained parameter distributions are Gaussian. Measurements are performed to test the algorithms on real data collected for three ferromagnetic objects: a magnet, pipe and block. The magnet is easily localised, the pipe reasonably well. The block cannot be localised: its field variations cannot be distinguished from background field variations. Subsequent simulations show that using gradiometers improves the performances of the algorithms. The effects of a number of controllable parameters are evaluated.

关键词： computer vision and image processing techniques earth magnetic field hidden magnetic objects Gaussian distribution least squares analysis object detection Interpolation and function approximation (numerical analysis) magnetic fields concomitant disturbance least squares approximations object localisation Gaussian parameter distributions quadrupole extension Optical, image and video signal processing magnetic object detection Magnetostatics magnetic dipole Other topics in statistics

来源：评论

学校读者我要写书评

暂无评论

vision enabled robots have 'eyes' for you

引用

COMPUTING & CONTROL ENGINEERING JOURNAL 2005年第6期15卷 19-20页

作者： Winchester, S

A NEW GENERATION OF vision ENABLED ROBOTS IS ABLE TO MAKE DECISIONS BASED ON SENSORY FEEDBACK FROM THEIR ENVIRONMENT. THEY CAN ADAPT TO PERHAPS ANY MANUFACTURING SCENARIO.

关键词： sensory feedback machine vision technology vision enabled robots Control applications in manufacturing processes robot vision Robotics Control engineering computing manufacturing environment image sensors industrial robots computer vision and image processing techniques industrial control image sensors

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：