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Inspection Method of Track Facilities Using image Analysis of images Taken from Front of Trains

Quarterly Report of RTRI (Railway Technical Research Institute) 2023年第3期64卷 205-210页

作者： Nagamine, Nozomi Goda, Wataru Maeda, Riho Tsubokawa, Yosuke Kato, So Itoi, Kensuke Head of Image Analysis Laboratory Information and Communication Technology Division Research Areas: Computer Vision Image Processing Signalling Systems Japan Image Analysis Laboratory Information and Communication Technology Division Research Areas: Computer Vision Image Processing Japan Head of Track Geometry and Maintenance Laboratory Track Technology Division Research Areas: Track Measuring Japan Track Geometry and Maintenance Laboratory Track Technology Division Research Areas: Track Measuring Japan Research Areas: Track Measuring Japan

Appropriate maintenance of tracks is vital for the safe operation of railways. Properly managing track facilities is necessary to prevent buckling of rails. Changes in society are creating a shortage of workers, a decrease in skilled engineers, a decrease in passenger income, and an increase in the need to develop low-cost inspection methods which do not require experience. Therefore, we have developed a method using only inexpensive camcorders, which can extract information from images to detect joint gaps, wooden sleeper deterioration and ballast shape, and estimate the kilometer point of these images to locate the installations in question. This paper describes the outline of the method and its application results. © 2023 Ken-yusha Inc.. All rights reserved.

关键词： Inspection

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Resolving ambiguity in depth extraction for motion capture using genetic algorithm

Resolving ambiguity in depth extraction for motion capture u...

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Congress on Evolutionary Computation

作者： Yin Yee Wai Chi Kin Chow Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Sha Tin Hong Kong China

There is considerable interest in motion capture from an image sequence taken from a video camera. However, since the images only consist of 2D information, the distance of an object from the image plane cannot be determined uniquely unless some constraints are imposed. Coplanar motion is a popular constraint adopted for this purpose. If the captured motion is not coplanar, only two possible solutions can be obtained at the best even the actual size of the object is given. Therefore, the motion cannot be captured without resolving the distances of each control point from the image plane. By assuming smooth transition, the problem is formulated as one minimizing the transition between image frames and the application of GA to solve this optimization problem is proposed.

关键词： Genetic algorithms Humans Cameras image resolution image sequences Animation Motion analysis Optical filters Optical recording Optical sensors

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Varying pose face recognition using combination of discrete cosine & wavelet transforms

Varying pose face recognition using combination of discrete ...

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International Conference on Intelligent and Advanced Systems, ICIAS

作者： Seyed Omid Shahdi S. A. R. Abu-Bakar Computer Vision Video and Image Processing (CvviP) Research Laboratory Faculty of Electrical Engineering Universiti Teknologi Malaysia Skudai Johor Malaysia

Requirement for a person to face a camera for face identification process may no longer be necessary if the face recognition system is robust against variation of facial pose. In this paper, we proposed a face recognition method which remains reliable even in very large head pose variations. In this method, feature from local regions of face are extracted after employing both discrete cosine transform and discrete wavelet transform. Learning strategy is then applied to infer the relationship between face in a given pose and its frontal view. Results we obtained are very promising considering that our proposed method solely relies on a single gallery image. We also demonstrated the high performance of our method in a condition whereby the face images are of low-resolution quality.

关键词： Face Face recognition Vectors Discrete cosine transforms Discrete wavelet transforms Feature extraction Databases

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Semantic segmentation using regions in natural scenes

Semantic segmentation using regions in natural scenes

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2011 International Conference on Electronic and Mechanical Engineering and Information Technology, EMEIT 2011

作者： Wu, Shilin Zhu, Feng Hao, Yingming Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Graduate School Chinese Academy of Sciences Beijing 100049 China Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Sciences Shenyang 110016 China Key Laboratory of Image Understanding and Computer Vision Liaoning Province 110016 China

ISBN: (纸本)9781612840857

By introducing an over-segmentation algorithm into the conditional model (CM), we propose a new region-based CM model (R-CM), and investigate its performance on semantic segmentation of images. In order to incorporate structure information of objects, we segment an image into regions by using an over-segmentation algorithm. Based on the results of CM model, we first consider assigning all pixels in one region with the same label, and then other feature potentials are included to counteract the influence of false over-segmentation. We compare our results to related work on the Olive & Torralba database and show that aside from improved accuracy of the whole database, our model obtains a perceptual improvement, with boundary of different objects correctly labeled. © 2011 IEEE.

关键词： Semantic Segmentation

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Multiple class segmentation using a scene-based framework

Multiple class segmentation using a scene-based framework

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2011 International Conference on Electronics and Optoelectronics, ICEOE 2011

作者： Wu, Shilin Zhu, Feng Miao, Xikui Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Graduate School of Chinese Academy of Sciences Beijing 100049 China Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Sciences Shenyang 110016 China Key Laboratory of Image Understanding and Computer Vision Liaoning Province 110016 China

ISBN: (纸本)9781612842738

In this paper, we propose a new scene-based conditional model and investigate its performance on multiple class segmentation of images. By including the scene of an image, we also propose a new texture-environment potential to represent texture environment of a pixel. We compare our results to related work on the Olive & Torralba database and show that our model obtains greatly improved accuracy of the whole database. More significantly, a large perceptual improvement is gained, i.e. details of different objects are correctly labeled. © 2011 IEEE.

关键词： image segmentation

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What Can an image of a Smooth Lambertian Surface Tell About Camera Nonlinearity?

What Can an Image of a Smooth Lambertian Surface Tell About ...

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Canadian Conference on computer and Robot vision, CRV

作者： Moumen T. El-Melegy Aly A. Farag Electrical Engineering Department Assiut University Asyut Egypt Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

This paper investigates the use of a single image of a smooth Lambertian surface to calibrate and remove some image nonlinearities due to the imaging device. To the best of our knowledge, this has not been addressed before in the literature. We show that this is possible, both theoretically and practically, taking advantage of some local shading measures that vary nonlinearly as a function of luminance and geometric nonlinearities (e.g., gamma correction and lens distortion). This can work as a basis for developing a simple method to estimate these nonlinearities from a single image. Several experiments are reported to validate the proposed method.

关键词： Cameras Distortion measurement Lenses Calibration Shape Lighting Surface treatment

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Optimization on unbounded solution space using dynamic genetic algorithms

Optimization on unbounded solution space using dynamic genet...

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International Joint Conference on Neural Networks (IJCNN)

作者： Chi Kin Chow Hung Tat Tsui Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Sha Tin Hong Kong China

ISBN: (纸本)0780370449

The problem of applying genetic algorithm (GA) to solve an optimization problem over an unbounded solution space is addressed. We propose to first transform the possible range of each parameter in the chromosome to a finite range with a nonlinear mapping such that the search on unbounded solution space becomes a search for high precision solution in a finite range. Modifications on the GA have been found necessary after such nonlinear mapping. As a result, a new GA with dynamic mutation range that facilitates coarse-refine search has been developed.

关键词： Genetic algorithms Biological cells Optimization methods Genetic mutations computer vision image processing Laboratories Genetic engineering Chromosome mapping Dynamic range

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DIRECT METHOD FOR SHAPE RECOVERY FROM POLARIZATION AND SHADING

DIRECT METHOD FOR SHAPE RECOVERY FROM POLARIZATION AND SHADI...

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IEEE International Conference on image processing

作者： Ali H. Mahmoud Moumen T. El-Melegy Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Electrical Engineering Department Assiut University Assiut Egypt

Polarization imaging can give information about surface shape, and roughness. Polarization has been used for shape recovery, but with convex/concave reconstruction ambiguity. In this paper, we present a direct method to shape recovery using both polarization and shading that resolves this ambiguity, without the need for nonlinear optimization routines. Several experiments on synthetic and real datasets are reported to evaluate the proposed method. The method consistently outperforms some well-known methods based on polarization information alone.

关键词： Shape Surface reconstruction Azimuth image reconstruction Surface treatment Cameras

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Heat Kernels for Non-Rigid Shape Retrieval: Sparse Representation and Efficient Classification

Heat Kernels for Non-Rigid Shape Retrieval: Sparse Represent...

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Canadian Conference on computer and Robot vision, CRV

作者： Mostafa Abdelrahman Moumen El-Melegy Aly Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Electrical Engineering Department Assiut University Asyut Egypt

One of the major goals of computer vision and machine intelligence is the development of flexible and efficient methods for shape representation. This paper presents an approach for shape retrieval based on sparse representation of scale-invariant heat kernel. We use the Laplace-Beltrami eigen functions to detect a small number of critical points on the shape surface. Then a shape descriptor is formed based on the heat kernels at the detected critical points for different scales, combined with the normalized eigen values of the Lap lace-Beltrami operator. Sparse representation is used to reduce the dimensionality of the calculated descriptor. The proposed descriptor is used for classification via the collaborative representation-based classification with regularized least square algorithm. We compare our approach to two well-known approaches on two different data sets: the nonrigid world data set and the SHREC 2011. The results have indeed confirmed the improved performance of the proposed approach, yet reducing the time and space complicity of the shape retrieval problem.

关键词： Shape Heating Eigenvalues and eigenfunctions Kernel Vectors Manifolds Heat transfer

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Frequency domain feature-based face recognition technique for different poses and low-resolution conditions

Frequency domain feature-based face recognition technique fo...

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Seyed Omid Shahdi S.A.R. Abu-Bakar Computer Vision Video and Image Processing (CvviP) Research Laboratory Faculty of Electrical Engineering Universiti Teknologi Malaysia Skudai Johor Malaysia

Pose variations are known to give real challenges in face recognition system. In this paper we proposed a method to recognize non-frontal faces with high performance by relying only on single full frontal gallery faces. By utilizing only small regions of the face or patches, we compute the Fourier coefficients of these patches for each image and transform them into a single vector. Hence, instead of comparing and matching pixels values we use these vectors to form a linear relationship which is then used to estimate the frontal face vector and then compare it with the actual frontal feature vector. The results show an average performance accuracy of 90% across all pose.

关键词： Face Face recognition Databases Feature extraction Training Vectors

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