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检索条件"任意字段=2nd International Conference on Computer Vision and Image Processing, CVIP 2017"

共 1800 条记录，以下是51-60 订阅

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Case Study for Graph Signal Denoising by Graph Structure Similarity 2

Case Study for Graph Signal Denoising by Graph Structure Sim...

引用

2nd international conference on image, vision and Computing (ICIVC)

作者： Song, Dao-Bang Zhang, Jiu-Wen Zhou, Jing Lanzhou Univ Sch Informat Sci & Engn Lanzhou Gansu Peoples R China

ISBN: (纸本)9781509062386

We study the denoising performance of several graph wavelet filter banks and image modeling with graph to enhance understanding of the relationship between graph signals and underlying structure. We design a new metric for measuring graph structure similarity (GSSIM) to evaluate those methods. GSSIM is positively related to PSNR as an index of corrupted signal with an additive Gaussian noise in the references and it is aware of graph structure. Subgraph-Based filter banks are superior to others in graph signal denoising. We introduce the idea of group-based approaches by removing edges between different groups, a set of communities with similar average. It can improve the signal to noise ratio substantially and reduce the high frequency loss. We demonstrate GSSIM is promise through intuitive examples. Group-based analysis improves the denoising effect of all the methods studied.

关键词： graph structure similarity community detection graph signal processing denoising image modeling

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The vision guidance and image processing of AGV 2

The vision guidance and image processing of AGV

引用

2nd Annual international conference on Information System and Artificial Intelligence (ISAI)

作者： Feng, Tongqing Jiao, Bin Shanghai Dian Ji Univ Elect Engn Coll 300 Blooms Rd Shanghai Peoples R China

Firstly, the principle of AGV vision guidance is introduced and the deviation and deflection angle are measured by image coordinate system. The visual guidance image processing platform is introduced. In view of the fact that the AGV guidance image contains more noise, the image has already been smoothed by a statistical sorting. By using AGV sampling way to obtain image guidance, because the image has the best and different threshold segmentation points. In view of this situation, the method of two-dimensional maximum entropy image segmentation is used to solve the problem. We extract the foreground image in the target band by calculating the contour area method and obtain the centre line with the least square fitting algorithm. With the help of image and physical coordinates, we can obtain the guidance information.

关键词： image segmentation

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A Simple and Effective Still image Retrieval Paradigm

A Simple and Effective Still Image Retrieval Paradigm

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2nd international conference on computer Science and Network Technology (ICCSNT)

作者： Liu, Wei Ma, Yujing Li, Wenhui Wang, Wei Liu, Yan Changchun Univ Coll Comp Sci & Technol Changchun Peoples R China

ISBN: (纸本)9781467329644;9781467329637

Considering a classic image-retrieval problem, a user submits a set of index images to a system and through repeated interactions, the goals are narrowed to the image(s) that satisfies the user. To this purpose, conventional content-based image retrieval (CBIR) paradigm make uses of image processing and computer-vision techniques, and tries to understand the visual(color, shape, texture etc) image content. We propose a novel paradigm to this problem from a totally different angle. It attempts to use the human's intuition capabilities. Instead of processing images, the system simply accumulates records of user feedback and recycles them in the form of collaborative filtering, just like a purchase recommendation system such as Amazo web. we use paradigm by a term "content-free" image retrieval (CFIR). We discuss many issues of visual retrieval, argue for the idea of CFIR, and present results of experiment. The experiment results show that the performance of CFIR improve image performance.

关键词： content-free visual retrieval collaborative filtering relevance feedback image similarity

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A novel text localization scheme for camera captured document images 2nd

A novel text localization scheme for camera captured documen...

引用

2nd international conference on computer vision and image processing, cvip 2017

作者： Khan, Tauseef Mollah, Ayatullah Faruk Department of Computer Science and Engineering Aliah University Kolkata700156 India

ISBN: (纸本)9789811078941

In this paper, a hybrid model for detecting text regions from scene images as well as document image is presented. At first, background is suppressed to isolate foreground regions. Then, morphological operations are applied on isolated foreground regions to ensure appropriate region boundary of such objects. Statistical features are extracted from these objects to classify them as text or non-text using a multi-layer perceptron. Classified text components are localized, and non-text ones are ignored. Experimenting on a data set of 227 camera captured images, it is found that the object isolation accuracy is 0.8638 and text non-text classification accuracy is 0.9648. It may be stated that for images with near homogenous background, the present method yields reasonably satisfactory accuracy for practical applications. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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Robust image Hashing Technique for Content Authentication based on DWT

Robust Image Hashing Technique for Content Authentication ba...

引用

1st international conference on computer vision and image processing (cvip)

作者： Vadlamudi, Lokanadham Naidu Vaddella, Rama Prasad V. Devara, Vasumathi Sree Vidyanikethan Engn Coll Informat Technol Tirupati 517102 AP India Sree Vidyanikethan Engn Coll Comp Sci & Engn Tirupati 517102 AP India JNT Univ JNTU Coll Engn Comp Sci & Engn Hyderabad 500085 TS India

ISBN: (纸本)9789811021046;9789811021039

This paper presents an image hashing technique for content verification using Discrete Wavelet Transform (DWT) approximation features. The proposed technique converts resized RGB color images to L*a*b* color images. Further, images are regularized using Gaussian low pass filter. A level 2, 2D DWT is applied on L* component of L*a*b* color image and the LL2 approximation sub-band image is chosen for feature extraction. The features are extracted by utilizing a sequence of circles on approximation sub-band image. Finally, the robust binary hash is generated from extracted features. The experimental results indicate that the hash of the presented technique is invariant to standard content preserving manipulations and malicious content altering operations. The experiment results of Receiver Operating Characteristics (ROC) plots indicate that the presented technique shows strong discriminative and robustness capabilities. Besides, the hash of the proposed technique is shorter in length and key dependent.

关键词： image authentication image hashing Discrete Wavelet Transform Approximation features Robustness

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Feature Extraction for image Recognition and computer vision

Feature Extraction for Image Recognition and Computer Vision

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2nd IEEE international conference on computer Science and Information Technology

作者： Jiang, Xudong Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

ISBN: (纸本)9781424445189

Feature extraction and classifier design are two main processing blocks in all pattern recognition and computer vision systems. For visual patterns, extracting robust and discriminative features from image is the most difficult yet the most critical step. Several typical and advanced approaches of feature extraction from image are explored, some of which are analyzed in depth. Various techniques of feature extraction from image are organized in four categories: human expert knowledge based methods, image local structure based approaches, image global structure based techniques and machine learning based statistical approaches. We will show examples of applying these feature extraction approaches to solve problems of the image based biometrics, including fingerprint verification/identification and face detection/recognition. These illustrative application examples unveil the ideas, principles and advancements of feature extraction techniques and demonstrate their effectiveness and limitations in solving real-world problems.

关键词： Feature extraction

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An Approach to Get Overall Emotion from Comment Text towards a Certain image Uploaded to Social Network Using Latent Semantic Analysis 2

An Approach to Get Overall Emotion from Comment Text towards...

引用

2nd international conference on image, vision and Computing (ICIVC)

作者： Wickramaarachchi, Wiraj Udara Kariapper, R. K. A. R. Wuhan Univ Technol Sch Comp Sci & Engn Wuhan Hubei Peoples R China Sabaragamuwa Univ Sri Lanka Dept Comp & Informat Syst Belihuloya Sri Lanka

ISBN: (纸本)9781509062386

One significant method of expressing the opinion of the users of social network is expressing true feelings or emotions through chats and comments for images, status or videos that has been uploaded to social network. This will increases the effectiveness of the communication among users since they have no face-to-face interaction. Text processing techniques are used to identify emotion which expressed through text. The research proposes an approach to get overall emotion from comment text towards an image, which uploaded to social network. The new methodology was developed as an enhanced extension of the previous works and using appropriate improvement and extension to them with Latent Semantic Analysis (LSA) because previous researches have proven that LSA is a light weight approach. And it is believed that, online emotion predicting systems must be light weight. The research achieved more efficiency than previous works due to light weight of the methodology, also introduced a prototype of GUI. Also the topic is open for future enhancement.

关键词： latent semantic analysis natural language processing emotion identification text processing social network

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Autofocus Window Selection Algorithm Based on Visual Saliency 2

Autofocus Window Selection Algorithm Based on Visual Salienc...

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2nd international conference on image, vision and Computing (ICIVC)

作者： Wei, Zhaoqi Su, Xiuqin Chinese Acad Sci Xian Inst Opt & Precis Mech Xian Shaanxi Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781509062386

Aiming at the problem of Autofocus window selection in imaging system, a new algorithm based on visual saliency for Autofocus window selection is proposed, which provides a new solution. A re-designed Itti model is used to predict the salient region in the visual scene. By choosing the local maxima in the saliency map to be the seed, the most salient region can be obtained by growing around it and a minimum enclosing rectangle can be found as the focus window. In this paper, the focus window selection based on visual saliency can efficiently capture the visual salient region and the position of general target well, highlight potential focus targets and improves the accuracy of focusing. Compared with the common focusing window selection algorithm, the method proposed in this paper can improve the focusing performance of the imaging system and has wider applicability in the general scene.

关键词： auto-focus window selection algorithm visual saliency computer vision self-adaptability

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Deep Convolutional Networks Super-Resolution Method for Reconstructing High Frequency Information of the Single image 2

Deep Convolutional Networks Super-Resolution Method for Reco...

引用

2nd international conference on image, vision and Computing (ICIVC)

作者： Zhao, Mandan Cheng, Chuanqi Zhang, Zhenjie Hao, Xiangyang Informat Engn Univ Sch Nav & Aerosp Engn Zhengzhou Henan Peoples R China

ISBN: (纸本)9781509062386

Super-resolution image reconstruction is one of the important issues in the field of computer vision. Machine learning is also the powerful method to solve the problem of computer vision. The method of SRCNN, which is put forward by Tang, is used for image super-resolution and shows the state-of-the-art performance. However, the method of SRCNN still has some shortcomings. On one hand, the training network convergence is slow and one trained network can only handle one settled scale factor model. Meanwhile, the input and output of the network contains a large number of the same information. It could lead to redundant training. On the other hand, the accuracy of the super-resolution reconstruction needs to be further improved. In order to improve these weaknesses and inspired by the network of the VGG and Res Net, we propose the method to restore the high frequency information of the image based on the residual network and enlarge the range of the effective vision perception based on very deep convolutional network. Through these improvements, we speed up the convergence rate of the training and improve the super-resolution image reconstruction accuracy. Especially some areas such as image detail and depth discontinuity have good performance. These improvements can furtherly optimize the single image super-resolution method, and expand its application scope. In the end, comparing with several advanced methods, such as SRCNN though the experiment, we confirm the validity and practicability of the improved strategy.

关键词： image super-resolution frequency information convolutional neural networks residual nerwork

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An efficient algorithm for medical image fusion using nonsubsampled shearlet transform 1

引用

2nd international conference on computer vision and image processing, cvip 2017

作者： Vishwakarma, Amit Bhuyan, M.K. Iwahori, Yuji Indian Institute of Technology Guwahati Guwahati781039 India Department of Computer Science Chubu University KasugaiAichi487-8501 Japan

ISBN: (数字)9789811078958

ISBN: (纸本)9789811078941

Multimodal medical image fusion techniques are utilized to fuse two images obtained from dissimilar sensors for obtaining additional information. These methods are used to fuse computed tomography (CT) images with magnetic resonance images (MRI), MR-T1 images with MR-T2 images, and MR images with single photon emission computed tomography (SPECT) images. In proposed method, nonsubsampled shearlet transform (NSST) is used for decomposition of source images to attain the low-frequency and high-frequency bands. The low-frequency bands are fused using weighted saliency-based fusion criteria, and high-frequency bands are fused with the help of phase stretch transform (PST) features. Applying inverse NSST operation, fused image is obtained. The results show the proposed method produces better results compared to state-of-the-art methods. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Magnetic resonance

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