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International Conference on Computational Intelligence and Security

作者： Peipei Pan Xin Zheng Qingqing Xu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing P.R. China

In this paper, we propose a novel approach for image completion with automatic structure propagation. This method integrates two stages: Firstly, it extends the salient structure lines from the known regions to the unknown by following a local self-similarity assumption on natural images. Then guided by the structure information, it restores the missing region by patch-based texture synthesis. Experiment results demonstrate a better effect of our method than that of the previous patch-based texture synthesis image completion algorithm.

关键词： image edge detection image segmentation image reconstruction image resolution Filling image restoration Sun

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Multi-sensor measurement adaptive filtering algorithm in measurement uncertainty

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Journal of Information and Computational Science 2012年第4期9卷 843-851页

作者： Hu, Zhentao Fu, Chunling Liu, Xianxing Laboratory of Image Processing and Pattern Recognition Henan University Kaifeng 475004 China Basic Experiment Teaching Center Henan University Kaifeng 475004 China

The reliable estimation of system state in multi-sensor uncertainty is always the hot and knotty issue of nonlinear filtering theory. Aiming to the reasonable utilization of measurement information, a novel multi-sensor measurement adaptive filtering algorithm is proposed in this paper. Firstly, Combining with the construction of measurement likelihood and maximize principle, the equivalent measurement are affirmed. Next, the selection and fusion of measurement without disturbance influence are accomplished by the introduction of statistic distance among the measurements, which can realize the optimization of equivalent measurement to some extend. The new method improves the adverse influence of disturbance in multi-sensor information fusion process, and retains the litter computational complexity relative to the distributed fusion structure. The theoretical analysis and experimental results show the efficiency of the proposed algorithm. Copyright © 2012 Binary Information Press.

关键词： Extended Kalman filters

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A robust hybrid approach for text line segmentation in historical documents

A robust hybrid approach for text line segmentation in histo...

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International Conference on pattern recognition

作者： Christian Clausner Apostolos Antonacopoulos Stefan Pletschacher Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Salford Greater Manchester UK

Large-scale digitisation of historical documents demands robust methods that cope with the presence of frequent distortions and noisy artefacts. This paper presents a hybrid text line segmentation method that uses a novel data structure and a rule base to combine the strengths of top-down and bottom-up approaches while minimising their weaknesses. The effectiveness of the proposed approach has been methodically evaluated in the context of large-scale digitisation using a standardised framework. Results on a diverse dataset show improved performance over top-down and bottom-up approaches as well as over a leading commercially available system.

关键词： Robustness image segmentation Data structures Libraries Merging Noise Layout

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A novel and fast method for precise license plate location from digital images based on fusion of salient features

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第19期6卷 511-519页

作者： Wang, Ran Wang, Guoyou Liu, Jianguo Chen, Zhong Shi, Yu Image Processing and Intelligent Key Laboratory of Ministry of Education of China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 730074 China

The license plate location technique is an important image processing step in license plate recognition system. Vehicle license plates are distinguished from backgrounds using features proposed in existing literatures. However, the effect of location is quite affected by feature selection. In this paper, we propose a method of precise license plate location fusing salient features. The method is mainly divided into three steps. First, candidate license plate regions are detected using improved Harris corner feature with much less time than traditional method. Then, candidates are sifted to only retain license plates based on two salient features named color combination and mean difference which are first proposed in this paper. Finally, the license plates are located precisely according to the projection feature. In experiment, the proposed algorithm was tested with 1942 real images captured in different environment and the license plates are successfully located as 97.6% in average with only 109ms. The experiment results demonstrates the effectiveness and efficient of our algorithm.

关键词： image processing

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Detection of Billet Character in Complex Production Line Scene

Detection of Billet Character in Complex Production Line Sce...

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第三届数字制造与自动化国际会议

作者： Hong Hanyu Yu Zhejun Zhang Xiuhua Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

Character information is hard to detect in billet scene images by CCD camera. In this paper, we present a method for detection of billet characters from measurements of recursive segmented image. This recursive segmented method can be used in a wide variety of billet scenes. According to high temperature and complex scene in the rolling line, we use an effective clustering and projection characteristics to determine the terminal condition of recursive segmentation. Then we can label character candidate regions in turn by this effective characteristics, and select the regions we want to achieve. The experiments show that this method makes full use of the characteristics of region and clustering. It can improve the quality of detection, and the detection result meets the need of practical application.

关键词： image processing production line billet character

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Person re-identification across multi-camera system based on local descriptors

Person re-identification across multi-camera system based on...

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ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC

作者： Qiao Huang Jie Yang Yu Qiao Institute of Image Processing and Pattern Recognition and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

Tracking the same person across multiple cameras is an important task in multi-camera systems. It is also desirable to re-identify the individuals who have been previously seen with a single-camera. This paper addresses this problem by the re-identification of the same individual in two different datasets, which are both challenging situations from video surveillance system. In this paper, local descriptors are introduced for image description, and support vector machines are employed for high classification performance and so an efficient Bag of Features approach for image presentation. In this way, robustness against low resolution, occlusion and pose, viewpoint and illumination changes is achieved in a very fast way. We get promising results from the evaluation with situations where a number of individuals vary continuously from a multi-camera system.

关键词： Vocabulary Cameras Histograms Feature extraction image color analysis Support vector machine classification Kernel

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Detection of Billet Character in Complex Production Line Scene

Detection of Billet Character in Complex Production Line Sce...

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International Conference on Digital Manufacturing and Automation (ICDMA)

作者： Hong Hanyu Yu Zhejun Zhang Xiuhua Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan China

关键词： Billets image segmentation Steel Arrays Filtering Licenses

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Enhancement of organ of interest via background subtraction in cone beam rotational angiocardiogram

Enhancement of organ of interest via background subtraction ...

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IEEE International Symposium on Biomedical Imaging

作者： Mingqing Chen Yefeng Zheng Kerstin Mueller Christopher Rohkohl Guenter Lauritsch Jan Boese Dorin Comaniciu Image Analytics and Informatics Siemens AG Corporate Research and Development USA Healthcare Sector Siemens AG Forchheim Germany Pattern Recognition Laboratory University of Erlangen-Nuremberg Germany

The real time X-ray angiography based on C-arm cone beam system is the workhorse imaging modality for interventional cardiac procedures. These images are two-dimensional (2D) projections of three dimensional (3D) objects along the X-ray direction. The organ of interest (OOI), such as left ventricle (LV) endocardium, in the projection image is superimposed with other anatomical structures and often has low contrast. In this study, a novel approach is proposed to isolate the OOI in projection images by subtracting with a background image, which is generated by numerical projection of 3D tomographic image with OOI masked out. Study based on one patient and one pig image is taken. About two to three-fold increase in the contrast-to-noise ratio (CNR) is achieved for LV endocardium, compared to an unprocessed image.

关键词： X-ray imaging image reconstruction Computed tomography Attenuation Angiography

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BP Neural Networks with Harmony Search Method-based Training for Epileptic EEG Signal Classification

BP Neural Networks with Harmony Search Method-based Training...

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International Conference on Computational Intelligence and Security

作者： Xiao-Zhi Gao Jing Wang Jarno M.A. Tanskanen Rongfang Bie Ping Guo College of Information Engineering Shanghai Maritime University China laboratory of Image Processing and Pattern Recognition Beijinz Normal University China Tampereen yliopisto - Hervannan kampus Tampere Pirkanmaa FI

In this paper, the Harmony Search (HS)-based BP neural networks are used for the classification of the epileptic electroencephalogram (EEG) signals. It is well known that the gradient descent-based learning method can result in local optima in the training of BP neural networks, which may significantly affect their approximation performances. Two HS methods, the original version and a new variation recently proposed by the authors of the present paper, are applied here to optimize the weights in the BP neural networks for the classification of the epileptic EEG signals. Simulations have demonstrated that the classification accuracy of the BP neural networks can be remarkably improved by the HS method-based training.

关键词： Electroencephalography Optimization Training Biological neural networks Feature extraction Epilepsy

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Classification of gothic and baroque architectural elements

Classification of gothic and baroque architectural elements

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International Conference on Systems, Signals and image Processing, IWSSIP

作者： Gayane Shalunts Yll Haxhimusa Robert Sablatnig Institute of Computer Aided Automation Computer Vision Laboratory University of Technology Vienna Austria Institute of Computer Graphics and Algorithms Pattern Recognition and Image Processing Lab University of Technology Vienna Austria

Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectural styles is viewed as a task of classifying separate architectural structural elements. In the scope of building facade architectural style classification the current paper targets the problem of classification of Gothic and Baroque architectural elements called tracery, pediment and balustrade. Since certain gradient directions dominate on the shape of each architectural element, discrimination between dominating gradients means classification of architectural elements and thus architectural styles. We use local features to describe gradient directions. Our approach is based on clustering and learning of local features and yields a high classification rate.

关键词： Shape Three dimensional displays Visualization Computer vision Histograms Windows

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