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检索条件"任意字段=Conference on Visual Communications and Image Processing 2007"

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Algorithms and techniques for image to sound conversion for helping the visually impaired people - Application proposal

Algorithms and techniques for image to sound conversion for ...

引用

14th International conference on Systems Signals and image processing, IWSSIP 2007 and 6th EURASIP conference Focused on Speech and image processing, Multimedia communications and Services, EC-SIPMCS 2007

作者： Cazan, Alexandru Vârbanescu, Radu Popescu, Dan Politehnica University of Bucharest 313 Splaiul Independentei Bucharest Romania

ISBN: (纸本)9789612480295

This paper presents a system that transforms images acquired with a camera into sounds. The system is designed for the visually impaired people and will convert real time images into sounds, respecting a certain algorithm, to preserve the visual information, but not forgetting the limitations imposed by the human hearing system. The resolution used for images to be conversed is to be found out after some future tests and statistics. The hardware implementation will have to use the capabilities of a portable device, such as a PDA or mobile phone or special built embedded system with microcontroller, and the images will be received though a small web-cam. Actual results obtained by this system configuration are to be evaluated within testing.

关键词： Audition

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Palmprint image quality measures in minutiae-based recognition

Palmprint image quality measures in minutiae-based recogniti...

引用

Joint Meeting of the 14th International Workshop on Systems, Signals and image processing/EURASIP conference Focused on Speech and image processing, Multimedia communications and Services

作者： Zheng, Yan Shi, GuangShun Wang, QingRen Zhan, Lin Nankai Univ Inst Machine Intelligence Tianjin 300071 Peoples R China Inst Criminol Technol Tianjin 300193 Peoples R China

ISBN: (纸本)9789612480363

The performance of a minutiae-based palmprint recognition system relies heavily on the quality of captured palmprint images. This paper introduces a block-based approach to evaluate the quality of a palniprint, in which two inter-block indices and four inner-block indices are developed. Inter-block quality indices includes block level orientation continuity, ridge thickness uniformity, while inner-block quality indices involve smudginess dryness judgment, the certainly of orientation in a block, ridge-valley frequency value, and special regions information. The final block quality value and image quality value are calculated based on these six indices. In experiment part, we evaluate the proposed measurement from three aspects: by comparing with human visual inspection, by observing the rise of Accuracy Rate after masking and by watching the relationship between GI value and final image quality value Q. These results show that our measurement can predict the quality of palmprint images accurately.

关键词： palmprint image quality minutiae orientation Accuracy Rate GI value

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EFFICIENT ACTIVE CONTOUR MODEL BASED ON VESE-CHAN MODEL AND SPLIT BREGMAN METHOD

EFFICIENT ACTIVE CONTOUR MODEL BASED ON VESE-CHAN MODEL AND ...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Yang, Yunyun Zhao, Yi Harbin Inst Technol Shenzhen Grad Sch Shenzhen 518055 Peoples R China

ISBN: (纸本)9781479902880

In this paper we propose an efficient multi-phase image segmentation for color images based on the piecewise constant multi-phase Vese-Chan model and the split Bregman method. The proposed model is first presented in a four-phase level set formulation and then extended to a multi-phase formulation. The four-phase and multi-phase energy functionals are defined and the corresponding minimization problems of the proposed active contour model are presented. The split Bregman method is applied to minimize the multi-phase energy functional efficiently. The proposed model has been applied to synthetic and real color images with promising results. The advantages of the proposed active contour model have been demonstrated by numerical results.

关键词： Active contour model multi-phase image segmentation split Bregman method level set method

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Improved PSP-Net Segmentation Network for Automatic Detection of Neovascularization in Color Fundus images

Improved PSP-Net Segmentation Network for Automatic Detectio...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Liu, Qiuming Wang, Shen Dai, Yulan Zhang, Jintao Wang, Yichen Zhou, Ruoxuan Jiangxi Univ Sci & Tech Sch Software Engn Ganzhou Jiangxi Peoples R China Cent South Univ Sch Comp Sci & Engn Changsha Peoples R China Jiangxi Normal Univ Sch Comp Info Engn Nanchang Jiangxi Peoples R China Nanchang Key Lab Virtual Digital Factory & Cultur Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781665475921

Proliferative Diabetic Retinopathy (PDR) is a serious retinal disease threatening diabetic patients. Intense retinal neovascularization in the retinal image is the most important clinical symptom of PDR, leading to visual distortion if not controlled. Accurate and timely detection of neovascularization from retinal images allows patients to receive adequate treatment to avoid further vision loss. In this work, we propose a retinal neovascularization automatic segmentation model based on improved Pyramid Scene Parsing Network (PSP-Net). To improve the accuracy of the model, we introduce the proposed channel attention module into the model. The network is evaluated with color fundus images from practice. Evaluation results show the network is superior to FCN, SegNet, U-Net and PSP-Net in accuracy and sensitivity. The model could achieve accuracy, sensitivity, specificity, precision and Jaccard similarity score of 0.9832, 0.9265, 0.9897, 0.9116 and 0.8501, respectively. This paper proves through plenty of experimental results that the network model is able to improve the accuracy of segmentation, relieve the workload of doctors, and is worthy of further clinical promotion.

关键词： fundus images image segmentation diabetic retinopath neovascularization deep learning

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High-frequency guided CNN for video compression artifacts reduction

High-frequency guided CNN for video compression artifacts re...

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IEEE International conference on visual communications and image processing (VCIP)

作者： Yu, Li Chang, Wenshuai Liu, Qingshan Gabbouj, Moncef Nanjing Univ Informat Sci & Technol Sch Comp Sci Nanjing Peoples R China Nanjing Univ Informat Sci & Technol Engn Res Ctr Digital Forens Minist Educ Nanjing Peoples R China Tampere Univ Dept Comp Sci Tampere Finland

ISBN: (纸本)9781665475921

In this paper, we propose a high-frequency guided CNN for video compression artifacts reduction. In the proposed method, high frequency component in Y channel is extracted and used to guide the quality enhancement of all Y, U, V channels. As high frequency component contains the edge and contour information of the objects in the image, which is of vital importance to both subjective and objective quality. In general, the proposed method consists of two modules: the high frequency guidance module and the quality enhancement module. The high-frequency guidance module uses multiple octave convolutions to extract the high-frequency component in Y channel and then fuse it into the features of Y, U, and V channels. While in the quality enhancement module, multiple CNN residual blocks are used for the quality enhancement of Y, U, and V channels. The proposed method was integrated into both HM-16.22 and VTM-16.0. The results on the JVET test sequence under All Intra configuration shows the effectiveness of the proposed method. Compared with HEVC, the proposed method achieves the average BD-rate reductions of -12.3%, -22.7% and -23.5% for Y, U and V channels respectively. Compared with VVC, the average BD-rate reductions are -6.7%, -12.3% and -13.2% correspondingly.

关键词： Deep Learning CNN High Frequency Video Coding Post-processing

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Disparity Estimation Algorithm for Stereo Video Coding Based on Edge Detecetion

Disparity Estimation Algorithm for Stereo Video Coding Based...

引用

International conference on Wireless communications and Signal processing

作者： Fan, Jingjing Liu, Feng Bao, Weibin Xia, Hongfei Nanjing Univ Posts & Telecommun Image Processing & Image Commun Jiangsu Key Lab Nanjing Peoples R China Zhengzhou Univ Technol Zhijiang Coll Hangzhou Peoples R China ZTE Telecorn Co Ltd Nanjing Peoples R China

ISBN: (纸本)9781424448562

Disparity estimation is an important technique in stereo video coding. This paper presents a disparity estimation algorithm based on edge detection. The algorithm makes full use of the human visual characteristics, that is, the human eye is more sensitive to the distortion of the edge region. Therefore, joint estimation is used for edge detection. The large code block size for coding the background region and the flat areas while small size for coding the edge region were used in this paper. Compared to the disparity estimation algorithm proposed in 181, the proposed algorithm can greatly improve the encoding speed of stereo video without affecting subjective image quality.

关键词： Stereo Video Disparity Estimation Motion Estimation Global Disparity Global Motion Human visual Characteristics

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Resolution enhancement through TARID processing

Resolution enhancement through TARID processing

引用

conference on visual communications and image processing 2002

作者： Schuler, JM Howard, JG Warren, PR Scribner, DA USN Res Lab Div Opt Sci Washington DC 20375 USA

ISBN: (纸本)0819444111

This paper outlines a generalized image reconstruction approach to improve the resolution of an Electro-Optic (EO) imaging sensor using multiple frames of an image sequence. This method only assumes the constituent video has some ambient motion between the sensor and stationary background, and the optical image is physically captured by a staring focal plane array.

关键词： Video Staring arrays image sensors Composites image processing Motion estimation Sensors Distortion image resolution Optical flow

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Fully Neural Network Mode Based Intra Prediction of Variable Block Size

Fully Neural Network Mode Based Intra Prediction of Variable...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Sun, Heming Yu, Lu Katto, Jiro Waseda Univ Waseda Res Inst Sci & Engn Tokyo Japan JST PRESTO 4-1-8 Honcho Kawaguchi Saitama Japan Zhejiang Univ Inst Informat & Commun Engn Hangzhou Peoples R China Waseda Univ Dept Comp Sci & Commun Engn Tokyo Japan

ISBN: (纸本)9781728180687

Intra prediction is an essential component in the image coding. This paper gives an intra prediction framework completely based on neural network modes (NM). Each NM can be regarded as a regression from the neighboring reference blocks to the current coding block. (1) For variable block size, we utilize different network structures. For small blocks 4x4 and 8x8, fully connected networks are used, while for large blocks 16x16 and 32x32, convolutional neural networks are exploited. (2) For each prediction mode, we develop a specific pre-trained network to boost the regression accuracy. When integrating into HEVC test model, we can save 3.55%, 3.03% and 3.27% BD-rate for Y, U, V components compared with the anchor. As far as we know, this is the first work to explore a fully NM based framework for intra prediction, and we reach a better coding gain with a lower complexity compared with the previous work.

关键词： Intra prediction image compression deep learning fully connected layer convolutional neural network

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Common spatial pattern discovery by efficient candidate pruning

Common spatial pattern discovery by efficient candidate prun...

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IEEE International conference on image processing (ICIP 2007)

作者： Yuan, Junsong Li, Zhu Fu, Yun Wu, Ying Huang, Thomas S. Northwestern Univ EECS Dept 2145 Sheridan Rd Evanston IL 60208 USA UIUC Beckman Inst Urbana IL 61801 USA

ISBN: (纸本)9781424414369

Automatically discovering common visual patterns in images is very challenging due to the uncertainties in the visual appearances of such spatial patterns and the enormous computational cost involved in exploring the huge solution space. Instead of performing exhaustive search on all possible candidates of such spatial patterns at various locations and scales, this paper presents a novel and very efficient algorithm for discovering common visual patterns by designing a provably correct and computationally efficient pruning procedure that has a quadratic complexity. This new approach is able to efficiently search a set of images for unknown visual patterns that exhibit large appearance variations because of rotation, scale changes, slight view changes, color variations and partial occlusions.

关键词： spatial pattern discovery image data mining approximate similarity matching candidate pruning

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Dual-layer visual vocabulary tree hypotheses for object recognition

Dual-layer visual vocabulary tree hypotheses for object reco...

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IEEE International conference on image processing (ICIP 2007)

作者： Ober, Sandra Winter, Martin Arth, Clemens Bischof, Horst Graz Univ Technol Inst Comp Graph & Vis A-8010 Graz Austria

ISBN: (纸本)9781424414369

This paper introduces an efficient method to substantially increase the recognition performance of a vocabulary tree based recognition system. We propose to enhance the hypothesis obtained by a standard inverse object voting algorithm with reliable descriptor co-occurrences. The algorithm operates on different layers of a standard k-means tree benefiting from the advantages of different levels of information abstraction. The visual vocabulary tree shows good results when a large number of distinctive descriptors form a large visual vocabulary. Co-occurrences perform well even on a coarse object representation with a small number of visual words. An arbitration strategy with minimal computational effort combines the specific strengths of the particular representations. We demonstrate the achieved performance boost and robustness to occlusions in a challenging object recognition task.

关键词： machine vision object recognition image databases tree data structures clustering methods

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