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An adapted point based tracking for vehicle speed estimation in linear spacing

An adapted point based tracking for vehicle speed estimation...

引用

International Conference on computer and Communication Engineering, ICCCE

作者： H. A. Rahim R. B. Ahmad A. S. M. Zain U. U. Sheikh School of Computer and Communication Engineering Universiti Malaysia Pedis Kangar Perlis Malaysia Computer Vision Video and Image Processing Research Laboratory (CVVIP) Department of Microelectronics and Computer Engineering Universiti Teknologi Malaysia Johor Bahru Johor Malaysia

Vehicle velocity estimation is an important aspect of intelligent transportation systems. Normally velocity is estimated using dedicated laser speed traps and Doppler radars. Recently, the use of cameras is becoming more common for the purpose of traffic surveillance and smart surveillance system. It is thus the aim of this paper to propose a method for vehicle speed estimation using these existing video cameras. In this paper, we propose a vehicle speed estimation method from video analysis. The method proposed contains several steps; image preprocessing, centroid extraction and tracking. The proposed method transforms the 2D image points into a 3D virtual world to obtain actual vehicle position in 3D space. This is to account for perspective distortion commonly seen in images. Using these 3D points and measuring the time for displacement, the vehicle speed is obtained. Experimental results have shown that the proposed method gives accurate velocity estimation.

关键词： Vehicles Estimation Surveillance Tracking Pixel Cameras Three dimensional displays

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Motion constraint patterns

Motion constraint patterns

引用

IEEE Workshop on Qualitative vision

作者： C. Fermuller Department for Pattern Recognition and Image Processing Institute for Automation Technical University of of Vienna Vienna Austria Computer Vision Laboratory Center for Automation Research University of Maryland College Park MD USA

The problem of egomotion recovery has been treated by using as input local image motion, with the published algorithms utilizing the geometric constraint relating 2-D local image motion (optical flow, correspondence, derivatives of the image flow) to 3-D motion and structure. Since it has proved very difficult to achieve accurate input (local image motion), a lot of effort has been devoted to the development of robust techniques. A new approach to the problem of egomotion estimation is taken, based on constraints of a global nature. It is proved that local normal flow measurements form global patterns in the image plane. The position of these patterns is related to the three dimensional motion parameters. By locating some of these patterns, which depend only on subsets of the motion parameters, through a simple search technique, the 3-D motion parameters can be found. The proposed algorithmic procedure is very robust, since it is not affected by small perturbations in the normal flow measurements. As a matter of fact, since only the sign of the normal flow measurement is employed, the direction of translation and the axis of rotation can be estimated with up to 100% error in the image measurements.< >

关键词： Motion estimation computer vision Automation image motion analysis Fluid flow measurement Motion measurement Rotation measurement Laboratories Educational institutions Geometrical optics

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The Infrared Multispectral image Simulation Research Based on 3D Scene

The Infrared Multispectral Image Simulation Research Based o...

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2013 3rd International Conference on Electric and Electronics(EEIC 2013)

作者： Bo Li Huai-ci Zhao Mei Du Jinfeng Lv Department of Optical-Electronics and Information Processing Shenyang Institute of automation Chinese Academy of Science University of Chinese Academy of Science Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Key Laboratory of Image Understanding and Computer Vision Shenyang Institute of Engineering

A method of generating infrared multispectral simulation images by 3D scene is presented. The infrared images at any observation angle of the scene and a data cube of simulation images of specific waveband could be generated by the method. Some experiments have been done in waveband 3～5μm to generate a data cube involving 401 infrared simulation images in the wavelength step 0.005μm, and the experiments results show that the simulation method presented in this paper could generate infrared multispectral images data cube rapidly. A way to reflect the differences while the observation angle changed is mentioned in this paper.

关键词： infrared multispectral simulation the data cube self-radiation

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OCCLUSAL SURFACE RECONSTRUCTION OF HUMAN TEETH FROM A SINGLE image BASED ON OBJECT AND SENSOR PHYSICAL CHARACTERISTICS

OCCLUSAL SURFACE RECONSTRUCTION OF HUMAN TEETH FROM A SINGLE...

引用

IEEE International Conference on image processing

作者： Aly Abdelrahim Aly Farag Shireen Elhabian Eslam Mostafa Wael Aboelmaaty Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Faculty of Dentistry Mansoura University Egypt Department of Oral Medicine and Periodontology University of Louisville Louisville KY USA

image formation involves understanding sensor characteristics and object reflectance. In dentistry, an accurate 3-D representation of the human jaw may be used for diagnostic and treatment purposes. Photogrammetry can offer a flexible, cost effective solution for accurate 3-D representation of the human teeth, which can be used for diagnostic and treatment purposes. Nonetheless there are several challenges, such as the non-friendly image acquisition environment inside the human mouth, problems with lighting and errors due to the data acquisition sensors. In this paper, we focus on the 3D surface reconstruction aspect for human teeth based on a single image. We introduce a more realistic formulation of the shape-from-shading (SFS) problem by considering the image formation components;the camera, the light source, and the surface reflectance. We propose a non-Lambertian SFS algorithm under perspective projection which benefits from camera calibration parameters. We take into account the attenuation of illumination due to near-field imaging. The surface reflectance is modeled using Oren-Nayar-Wolff model which accounts for the retro-reflection case. Our experiments provide promising quantitative metric results for the proposed approach.

关键词： Teeth Surface reconstruction Rough surfaces Surface roughness Cameras Humans image reconstruction

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Iterative data adaptive anisotropic image filtering

Iterative data adaptive anisotropic image filtering

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2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012

作者： Yang, Chang-Cai Zheng, Xin-Yi Tian, Jin-Wen Shang, Ke Tian, Xin Hao, Wei Institute for Pattern Recognition and Artificial Intelligence Science and Technology on Multi-Spectral Information Processing Laboratory Huazhong University of Science and Technology Wuhan 430074 China Electrical Engineering and Renewable Energy School China Three Gorges University Yichang 443002 China Institute of Intelligent Vision and Image Information College of Computer and Information Technology China Three Gorges University Yichang 443002 China

ISBN: (纸本)9781467314855

This paper presents a novel data-adaptive anisotropic filtering technique built on top of an iterative scheme. This new technique can preserve the original significant structures while suppressing noises to the largest extent. To achieve this goal, dominant orientation information of all gradients is used to control the local kernel adaptively. This results in elongated and elliptical contours spread along the directions of the local edge structure. With these locally adapted kernels, the smoothing is mostly effective along the edges, rather than across them. Therefore details in the original input can be preserved. The performance of the proposed data-adaptive anisotropic filter together with its iterative scheme are compared with the conventional Gaussian filter, anisotropic diffusion filter, the structure-adaptive anisotropic filter, and the iterative kernel regression scheme. The experimental results on both simulated Gaussian and Poission noisy images indicate that the proposed method performs the best, and the iterative scheme can significantly improve the performance of the noise suppressing while delivering high computation efficiency. © 2012 IEEE.

关键词： Iterative methods

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Automatic identification of lung abnormalities in chest spiral CT scans

Automatic identification of lung abnormalities in chest spir...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： A. El-Bazl A.A. Farag R. Falk R. La Rocca Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Medical Imaging Division Jewish Hospital USA Medical Imaging Division Jewish Hospital Kentuckiana Cancer Institute

Our aim is to develop a fully automatic computer-assisted diagnosis (CAD) system for lung cancer screening using chest spiral CT scans. A screening program on 1000 subjects aims at quantification of the effectiveness of low dose spiral CT scans for early diagnosis of lung cancer, and evaluation of its possible impact on improving the mortality rate of cancer patients. The paper presents an image analysis system for 3D reconstruction of the lungs and trachea, detection of lung abnormalities, identification/classification of these abnormalities with respect to specific diagnosis, and distributed visualization of the results over computer networks. We present two novel approaches for segmentation of the lung tissues from the surrounding structures in the chest cavity, and detection of abnormalities in the lungs. The segmentation algorithm is hierarchical, first isolating the background from the chest cavity, then isolating the lungs from surrounding structures (e.g., ribs, liver, and other organs). Abnormalities in the lungs are detected by analyzing the segmented lung tissues and extracting the isolated lumps that appear in various connected regions. 3D reconstructions are also generated for these abnormalities, to be used for subsequent identification/classification steps. Results on 50 subjects are shown, and have been evaluated against radiologists. Our image analysis approach has provided comparable results with respect to the experts. The approach is quite fast, and lends itself to distributed visualization over computer networks.

关键词： Lungs Spirals Computed tomography Cancer image analysis image reconstruction Visualization computer networks image segmentation computer aided diagnosis

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A Novel LOS Rate Estimation Method Based on images for Strap-down Inertial Guidance 3

A Novel LOS Rate Estimation Method Based on Images for Strap...

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2020 3rd International Conference on Advanced Algorithms and Control Engineering, ICAACE 2020

作者： Xu, Zheng Luo, Haibo Hui, Bin Chang, Zheng Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Science Shenyang110016 China Key Lab of Image Understanding and Computer Vision Shenyang110016 China

With the development of technology, precision guided weapon is becoming more and more important in modern war. In order to launch our recent guidance system on medium and small guided weapons, we propose a method to obtain the LOS rate by combining information from both camera and gyroscope. To be specific, we firstly calculate the body LOS angle through transforming the image pixel coordinate system into the image physical coordinate system according to camera internal parameters;then subtract the missile motion information contained in the measurement signal of the seeker and finally the LOS rate is deduced. Comparing with traditional gimballed seekers, our strap-down seekers with camera have significantly reduced costs and influences caused by external environments on platform. © Published under licence by IOP Publishing Ltd.

关键词： Cameras

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A kidney segmentation approach from DCE-MRI using level sets

A kidney segmentation approach from DCE-MRI using level sets

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： H. Abdelmunim Aly A. Farag W. Miller Mohamed AboelGhar Department of Computer Science Computational Biomedicine Laboratory University of Houston Houston TX USA Computer Vision and Image Processing LabDepartment of Electrical and Computer Engineering University of Louisville Louisville KY USA Medical School Mansoura University Mansoura Egypt

Acute rejection is the most common reason of graft failure after kidney transplantation, and early detection is crucial to survive the transplanted kidney function. Automatic classification of normal and acute rejection transplants from dynamic contrast enhanced magnetic resonance imaging (DCEMRI), is of great importance. Kidney segmentation is the first step for such classification. The image intensity inside the kidney is used as an indication of failure/success. Differentiating between different cases cases is implemented by comparing subsequential kidney scans signals. So, this process is mainly dependent on segmentation. This paper introduces a new shape-based segmentation approach based on level sets. Training shapes are collected from different real data sets to represent the shape variations. Signed distance functions are used to represent these shapes. The methodology incorporates image and shape prior information in a variational framework. The shape registration is considered the backbone of the approach where more general transformations can be used to handle the process. We introduce a novel shape dissimilarity measure that enables the use of different (inhomogeneous) scales. The approach gives successful results compared with other techniques restricted to transformations with homogeneous scales. Results for segmenting kidney images will be illustrated and compared with other approaches to show the efficiency of the proposed technique.

关键词： Level set image segmentation computer vision Magnetic resonance imaging Shape measurement Biopsy Biomedical computing computer science image processing Biomedical imaging

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A directional-progressive search method for infrared small target detection 3

A directional-progressive search method for infrared small t...

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3rd Optoelectronics Global Conference, OGC 2018

作者： Zhang, Xiangyue Ding, Qinghai Luo, Haibo Hui, Bin Chang, Zheng Zhang, Junchao Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Opto-Electronic Information Processing CAS Shenyang110016 China Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang110016 China Space Star Technology Co. Ltd Beijing100086 China

ISBN: (纸本)9781538673973

Infrared small target detection plays a key role in infrared precision guidance and infrared early-warning system. It has been a difficult problem for researchers to study on how to detect targets accurately at a long distance as early as possible. Most of the existing algorithms can detect small targets in simple backgrounds, but they would fail on the detection when the background clutters are chaotic and the signal to clutter ratio (SCR) is low. Therefore, we propose a new infrared small target detection method which called a directional-progressive search (DPS) method. Our method derives from a fact that a small target is an isotropic Gaussian distribution at a long distance, while clutters show different characteristics in different directions. Based on this difference, we decompose the original image into first-order sub-images with different directions by using a first-order directional derivative (FODD) filter. Then zero-crossing points are detected in each direction step by step to distinguish small targets and background clutters. After screening progressively, the positions where existing zero-crossing points in every sub-image can be confirmed as targets. Experimental results show that our method acquires higher detection rates and lower false alarm rates compared with other methods. At the same time, our method can still keep better performance under various complex backgrounds. The robustness of our method is strong. © 2018 IEEE.

关键词： Clutter (information theory)

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A variational framework for 3D colonic polyp visualization in virtual colonoscopy

A variational framework for 3D colonic polyp visualization i...

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IEEE International Conference on image processing

作者： Dongqing Chen Aly A. Farag Robert L. Falk Gerald W. Dryden Computer Vision & Image Processing (CVIP) Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY USA Jewish Hospital Louisville KY USA Division of Gastroenterology/Hepatology University of Louisville Louisville KY USA

Colorectal cancer includes cancer of the colon, rectum, anus and appendix. Since it is largely preventable, it is extremely important to detect and treat the colorectal cancer in the earliest stage. Virtual colonoscopy is an emerging screening technique for colon cancer. One component of virtual colonoscopy, image pre-processing, is important for colonic polyp detection/ diagnosis, feature extraction and classification. This paper introduces a general variational approach based framework for a computer aided diagnosis system for colorectal cancer. It includes techniques for 3D colon segmentation, 3D colon object reconstruction by iso-surface generation, and 3D centerline extraction. The proposed framework has been validated on 22 real CT colonography datasets.

关键词： Colonic polyps Visualization Virtual colonoscopy Cancer Colon Colonography image segmentation Optical computing Computed tomography image reconstruction

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