检索结果-内蒙古大学图书馆

作者： Zhu, Songhao Liu, Yuncai Institute of Image Process and Pattern Recognition Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9781424421756

Automatic image annotation is a promising way to achieve more effective image management and retrieval by using keywords. However, system performances of the existing state-of-the-art keyword annotation schemes are often not so satisfactory. Therefore, image annotation refinement is crucial to improve the imprecise annotation results. In this paper, a novel approach is developed to automatically refine the initial annotation of images. First, for a query image, the candidate annotations are obtained by a step-up model-based algorithm using perceptual visual characteristic. Then, a refine algorithm, fast random walk with restart is used to re-rank the candidate annotations and the top ones are reserved as the final annotations. Experiments conducted on the typical Corel dataset shows that the proposed scheme can effectively improve the automatic annotation performance. © 2008 IEEE.

关键词： image annotation

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Segmenting video shots using 2D entropy model

Segmenting video shots using 2D entropy model

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World Congress on Intelligent Control and Automation (WCICA)

作者： Songhao Zhu Yuncai Liu Institute of Image Process and Pattern Recognition Shanghai Jiaotong University Shanghai China

A shot presents a contiguous action recorded by an uninterrupted camera operation and frames within a shot keep spatio-temporal coherence. Segmenting a serial video stream file into meaning shots is the first pass for the task of video analysis, content-based video understanding. In this paper, a hierarchical framework based on an improved two-dimensional entropy model is proposed to complete the purpose of the partition of video shots. Our approach first selects the transition boundary candidates in the state of desampling. Then these detected transition candidates are further classified into cut or gradual type, and at the same time the falsely detected shot breaks can be distinguished and merged into the normal shot based on the human perception principle of visual content. Moreover, the boundary of gradual transition can be precisely located using characteristic features of gradual transition. A large number of video sequences are used to test our system performance and promising results have been obtained.

关键词： Entropy Pixel Video sequences Visualization Lighting Cameras Streaming media

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image annotation refinement using semantic similarity correlation

Image annotation refinement using semantic similarity correl...

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International Conference on pattern recognition

作者： Songhao Zhu Yuncai Liu Institute of Image Process and Pattern Recognition Shandong Jiaotong University Shanghai China

ISBN: (纸本)9781424421749

关键词： image retrieval Content based retrieval Digital images Testing pattern recognition Linear discriminant analysis Machine learning Support vector machines Support vector machine classification Web search

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A novel scheme for video scenes segmentation and semantic representation

A novel scheme for video scenes segmentation and semantic re...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Songhao Zhu Yuncai Liu Institute of Image Process and Pattern Recognition Shanghai Jiaotong University Shanghai China

Grouping video contents into semantic segments is the crucial pass to content-based video summarization and retrieval. In this paper, we present a novel scene segmentation and semantic representation scheme for various video types. We first detect video shot using a coarse-to-fine algorithm. The key frames without useful information are detected and removed using template matching. Spatio-temporal coherent shots are then grouped into the same scene based on the temporal constraint of video content and visual similarity of shot activity. With general editing technique used in the continuously recorded video, semantic representation of scene content is specified to satisfy human demand on video retrieval. The proposed algorithm has been performed on various types of videos containing movie and TV program. Promising experimental results shows that the proposed method makes sense to efficient retrieval of video contents of interest.

关键词： Correlation Integrated circuits Feature extraction Interviews Visualization Testing Histograms

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Automatic artist recognition of songs using a hierarchic structure

Automatic artist recognition of songs using a hierarchic str...

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China-Ireland International Conference on Information and Communications Technologies, CIICT 2007

作者： Zhu, Song-Hao Liu, Yun-Cai Institute of Image Process and Pattern Recognition Shanghai Jiao tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9780863418273

In this paper, we develop a hierarchic structure to complete the reorganization of artist automatically. This proposed system can efficiently identify the artist's voice of a raw song by analyzing substantive features extracted from both pure music and singing song mixed with accompanying music. The silent segments of a raw song are firstly detected and removed. Then, the pure music segments are distinguished from the segments of singing song mixed with accompanying music by support vector machines based on learning from the training data. Furthermore, the singing voice is recognized by the clustering results and the domain knowledge related to properties of the accompanying music and voice. The experiments on different genres of songs illustrate our proposed system is possible.

关键词： Music

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Car plate detection using cascaded tree-style learner based on hybrid object features

Car plate detection using cascaded tree-style learner based ...

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IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006

作者： Wu, Qiang Zhang, Huaifeng Jia, Wenjing He, Xiangjian Yang, Jie Hintz, Tom Computer Vision Research Group University of Technology Sydney PO Box 123 Broadway NSW 2007 Australia Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. China

ISBN: (纸本)0769526888

Car plate detection is a key component in automatic license plate recognition system. This paper adopts an enhanced cascaded tree style learner framework for car plate detection using the hybrid object features including the simple statistical features and Harr-like features. The statistical features are useful for simplifying the process.on cascade classifier. The cascaded tree-style detector design will further reduce the false alarm and the false dismissal while retaining a high detection ratio. The experimental results obtained by the proposed algorithm exhibit the encouraging performance. © 2006 IEEE.

关键词： Object recognition

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Car Plate Detection Using Cascaded Tree-Style Learner Based on Hybrid Object Features

Car Plate Detection Using Cascaded Tree-Style Learner Based ...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Qiang Wu Huaifeng Zhang Wenjing Jia Xiangjian He Jie Yang Tom Hintz Computer Vision Research Group University of Technology Broadway NSW Australia Institute of Image Process. & Pattern Recognition Shanghai Jiaotong University China

关键词： Object detection Licenses Detectors Computer vision pattern recognition Lighting Interference Australia image recognition Robustness

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A Combining Method for Tumors Detection from Near-infrared Breast Imaging

A Combining Method for Tumors Detection from Near-infrared B...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Zhicheng Wang Jian Liu Jinwen Tian Zeping Xie State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. & Tech. Wuhan 430074 China Key Lab. for Image Process. & Intelligent Control State Educ. Comm. School of Life Science & Technology Huazhong University of Science and Technology Wuhan China

This paper introduces the new qualitative and quantitative methods, which can diagnose breast tumors. Qualitative methods include blood vessel display inside and outside of pathological changes part of breast, display of equivalent pixel curves at the part of pathological changes and display of breast tumor image edge. Accordingly, three feature extraction operators are proposed, i.e. the combination operators of anisotropic gradient and smoothing operator, an improved Sobel operator and an edge sharpening operator. Furthermore, quantitative diagnostic approaches are discussed based on blood and oxygen contents according to abundant clinical data and pathological mechanism of breast tumors. The results of clinic show that the methods of combining qualitative and quantitative diagnose are effective for breast tumor images, especially for early and potential breast cancer

关键词： Breast tumors Displays Pathology Blood vessels Biomedical imaging Pixel Feature extraction Anisotropic magnetoresistance Smoothing methods Breast cancer

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Background removal in dental panoramic X-ray images by the A-Trous multiresolution transform

Background removal in dental panoramic X-ray images by the A...

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2005 European Conference on Circuit Theory and Design

作者： Goebel, Peter Michael Belbachir, Ahmed Nabil Truppe, Michael Fh-campus Wien Technical Project- and Process Management Ettenreichgasse 45a 1100 Vienna Austria Vienna University of Technology Pattern Recognition and Image Procesing Group Vienna Austria Karl Landsteiner Institute for Biotelematics Danube University Krems A-3500 Krems Austria

ISBN: (纸本)0780390660

Dental Panoramic X-ray images are images having complex content, because several layers of tissue, bone, fat, etc. are superimposed. Non-uniform illumination, stemming from the X-ray source, gives extra modulation to the image, which causes spatially varying X-ray photon density. The interaction of the X-ray photons with the density of matter causes spatially coherent varying noise contribution. Many algorithms exist to compensate background effects, by pixel based or global methods. However, if the image is contaminated by a non-negligible amount of noise, that is usually non-Gausslan, the methods cannot approximate the background efficiently. In this paper, a dedicated approach for the removal of a multiplying background is presented using polynomial scaling and the A-Trous multiresolution transform. The new method uses a background image and a diagnostic image together to estimate the density of the diagnostic content. It assumes a locally Gaussian statistic scaled by a hidden factor, where the hidden factor represents the variance of the non-Gaussian process.of image generation. Because, the method also removes noise from the compound signal, a comparison to a standard denoising method is given. This approach has been tested on 50 images from a database of panoramic X-ray images where the results are cross validated by medical experts.

关键词： Medical imaging

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Target detection in radar: Current status and future possibilities

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JOURNAL OF NAVIGATION 1997年第2期50卷 303-313页

作者： Li, VYF Miller, KM [a1 ](Hong Kong University of Science and Technology)[a2 ](Institute of Marine Studies University of Plymouth)Most of the radar systems used in operating marine vessel traffic management services experience problems such as track loss and track swap which may cause confusion to the traffic regulators and lead to potential hazards in the harbour operation. The reason is mainly due to the limited adaptive capabilities of the algorithms used in the detection process. The decision on whether a target is present is usually based on the amplitude information of the returning echoes. Such method has a low efficiency in discriminating between the target and clutter especially when the signal-to-noise ratio is low. With modern signal processing techniques more information can be extracted from the radar return signals and the tracking parameters of the previous scan. The objectives of this paper are to review the methods which are currently adopted in radar target identification identify techniques for extracting additional information and consider means of data analysis for deciding the presence of a target. Instead of employing traditional two-state logic it is suggested that the radar signal should be allocated in terms of threshold levels into fuzzy sets with its membership functions being related to the information extracted and the environment. Additional signal processing techniques are also suggested to explore pattern recognition aspects and discriminate features which are associated with a return signal from those of clutter.

Most of the radar systems used in operating marine vessel traffic management services experience problems, such as track loss and track swap, which may cause confusion to the traffic regulators and lead to potential hazards in the harbour operation. The reason is mainly due to the limited adaptive capabilities of the algorithms used in the detection process. The decision on whether a target is present is usually based on the amplitude information of the returning echoes. Such method has a low efficiency in discriminating between the target and clutter, especially when the signal-to-noise ratio is low. With modern signal process.ng techniques more information can be extracted from the radar return signals and the tracking parameters of the previous scan. The objectives of this paper are to review the methods which are currently adopted in radar target identification, identify techniques for extracting additional information and consider means of data analysis for deciding the presence of a target. Instead of employing traditional two-state logic, it is suggested that the radar signal should be allocated in terms of threshold levels into fuzzy sets with its membership functions being related to the information extracted and the environment. Additional signal process.ng techniques are also suggested to explore pattern recognition aspects and discriminate features which are associated with a return signal from those of clutter.

关键词： radar signal process.ng target detection

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