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检索条件"任意字段=International Congress on Image and Signal Processing, BioMedical Engineering and Informatics"

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A 3D Multi-scale Block LBP Filter for Lung Nodule Enhancement Based on the CT images 9

A 3D Multi-scale Block LBP Filter for Lung Nodule Enhancemen...

引用

9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Xu, Fan Zhang, Wen-Jing Li, Xin-Yue Xiao, Hu Peng, Shao-Hu Nam, Hyun-Do Zhang, Mian-Feng Guangzhou Univ Sch Mech & Elect Engn Guangzhou Guangdong Peoples R China Dankook Univ Dept Elect & Elect Engn Yongin South Korea Shantou Ctr Hosp Shantou Peoples R China

ISBN: (纸本)9781509037100

The computer-aided diagnostic (CAD) system can greatly influence the early detection of lung cancer in radiographs and computed tomography (CT) images, And the automatic nodule detection plays an important role in the CAD systems. This paper proposed a new enhancement filter (3D multi-scale Block LBP Filter) to detect the nodules in the lung regions. By taking advantages of the nodule regions' pixel value characteristics and shape features, the proposed filter is able to enhance the nodule-like regions and restrain the line-like regions and edge regions. Moreover, Integral image Technique (IIT) is applied accelerate the processing speed of the filter. Experimental results showed that the proposed filter can improve the accuracy and reduce the false positive.

关键词： CAD system 3D CT images 3D Multi-scale Block LBP filter nodule detection Integral image Technique

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Efficient Contrast Enhancement with Truncated Adaptive Gamma Correction 9

Efficient Contrast Enhancement with Truncated Adaptive Gamma...

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Huang, Lihui Cao, Gang Yu, Lifang Commun Univ China Sch Comp Sci Beijing 100024 Peoples R China Beijing Inst Graph Commun Beijing Key Lab Signal & Informat Proc High End P Beijing 102600 Peoples R China

ISBN: (纸本)9781509037100

Gamma correction is an efficient tool typically used to adjust the contrast and brightness of digital images. Recently, an adaptive gamma correction method is proposed by relating gamma parameter with the cumulative distribution function (CDF) of gray level histograms. It gains satisfied contrast enhancement (CE) effects on dimmed images, but is invalid on bright regions which are universal in real scenarios, such as excessive exposure, white objects and highlight regions. In order to attenuate such a deficiency, we propose an improved adaptive gamma correction algorithm in this paper. Instead of directly applying CDF curves as the gamma parameter, we truncate them by thresholding with a reasonable limit. Accordingly, contrast of input dimmed images could be improved without losing details in bright regions. Both qualitative and quantitative experimental results demonstrate the promising performance of our proposed CE method in enhancing the contrast and brightness of dimmed images.

关键词： contrast enhancement adaptive gamma correction dimmed image brightness histogram

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Visual perception features of color damage in High Definition video compression 9

Visual perception features of color damage in High Definitio...

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9th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2016

作者： Xu, Li Jiang, Xiuhua Information Engineering Communication University of China Beijing China

ISBN: (纸本)9781509037100

High Definition video color information research and analysis, mainly considering compression process brought about a decline in the quality of visual perception. Four subjective evaluation is designed and experiments has been done: The diversity of the human eye perception of time;rate selection;and two subjective evaluation experiments of the video with DSCQS as the standard. The High Definition video main characteristics of the human eye perception between color and compression rate injury. Before the experiment, statistical methods were used to calculate the actual sample size;according to R-REC-BT series of standards for subjective evaluation results of the statistical data after the experiment. Finally, analyzed the data results combined with color visual characteristics of the human eye. © 2016 IEEE.

关键词： Color

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An Improved SAM Algorithm For Red Blood Cells and White Blood Cells Segmentation 9

An Improved SAM Algorithm For Red Blood Cells and White Bloo...

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Hou, Xiyue Li, Qingli Wang, Qian Zhou, Mei Liu, Hongying East China Normal Univ Shanghai Key Lab Multidimens Informat Proc Shanghai 200241 Peoples R China

ISBN: (纸本)9781509037100

The segmentation of red blood cells and white blood cells has important research value in the field of rheological properties of blood and the pathogenesis of some diseases. And it is the reflection of bone hematopoietic state, blood diseases and other diseases. Especially for the diagnosis of blood diseases, the detection and prevention of treatment process, there is high value of clinical research. The separation of red blood cells and white blood cells using hyperspectral remote sensing image processing is a new field that it is essentially different from traditional multi spectral classification. Because of the different chemical composition and molecular space structure of red blood cells and white blood cells, it results in different spectrum. Each pixel of hyperspectral image can obtain a unique continuous spectral curve, and it can be compared with the spectral curves which are known to obtain target object. So the author designs a new analytical method which is based on the various processing methods of hyperspectral image. First of all, using the BandMax wizard to lock target image and band based on target detection;secondly, conducting differential search algorithm based on the blind signal;thirdly, using an improved algorithm-based on SAM combined with SID algorithm;finally, using advanced filtering method to get clearer image information. In this paper, it focuses on the effective extraction and improves the classification accuracy of white blood cells.

关键词： hyperspectral imaging image processing spectral angle mapping segmentation blood cell

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A Novel Fusion Method of Infrared and Visual images based on Undecimated Discrete Wavelet Transform and Saliency Map 9

A Novel Fusion Method of Infrared and Visual Images based on...

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Gan, Wei Chen, Honggang He, Xiaohai Ma, Minglang Sichuan Univ Coll Elect & Informat Engn Chengdu 610064 Peoples R China

ISBN: (纸本)9781509037100

This paper proposes a new fusion approach of infrared (IR) and visual (VIS) images based on Undecimated Discrete Wavelet Transform (UDWT) and saliency map analysis. The proposed fusion method is composed of three steps. Firstly, IR and VIS images are decomposed into low-pass sub-band coefficients and high-pass sub-band coefficients by UDWT. Meanwhile, sub-band directional coefficients are extracted by Non-Subsampled Directional Filter Banks (NSDFB) from high-pass sub-band coefficients. Secondly, the coefficient combination rules are set based on saliency maps of original IR and VIS images, which are obtained by employing the Itti saliency computing model. Thirdly, fused images are re-built by the inverse UDWT. The results of the experiments indicate that the presented approach achieves better subjective fusion effects than some current popular fusion methods. Furthermore, the proposed method gets better objective assessments.

关键词： image fusion infrared image undecimated discrete wavelet transform saliency map

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Attention State Assessment by Analyzing Electroencephalograph signals 9

Attention State Assessment by Analyzing Electroencephalograp...

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Zhao, Junchang Huang, Xiaolin Wang, Jun Nanjing Univ Posts & Telecomm Image Proc & Image Commun Key Lab Nanjing Jiangsu Peoples R China Nanjing Univ Sch Elect Sci & Engn Inst Biomed Elect Engn Nanjing 210093 Jiangsu Peoples R China

ISBN: (纸本)9781509037100

For brain function study, it is very important to assess the state of different attention conditions. In this paper, we study a cross-correlation between different attention electroencephalograph (EEG) signals by detrended cross-correlation analysis (DCCA). We use the method to study attention a wave EEG. And, we found that is possible to discriminate the cross-correlation between the meditation state of closing eyes and the absence of mind. It was found that the DCCA values of idle subjects' a wave EEG signals increased compared the meditating participants' a wave EEG signals. And it can be particularly helpful for treatment and brain development research.

关键词： DCCA a wave meditation activity

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Tuberculosis Bacteria Detection based on Random Forest using Fluorescent images 9

Tuberculosis Bacteria Detection based on Random Forest using...

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Zheng, Chi Liu, Jingxin Qiu, Guoping Univ Nottingham Sch Comp Sci Ningbo Zhejiang Peoples R China Univ Nottingham Sch Comp Sci Nottingham England

ISBN: (纸本)9781509037100

Tuberculosis (TB) is an infectious disease in low and middle-income countries. There are many methods of physical examinations for tuberculosis detection, but the most effective method is visual examination using microscopes, including fluorescent microscopy and bright field microscopy. However, according to the analysis of previous research work, the method based on fluorescent microscopes can yield on average 10% on sensitiveness than the bright field microscopy. In this paper, we present a TB detection method based on Random Forest using fluorescent microscopic images. We have conducted experiments on three types of classifiers, in terms of Random Forest (RF), linear SVM (LinSVM), and Cross-Validation SVM (CVSVM). The experimental results show that the machine learning method of Random Forest for TB segmentation and detection using fluorescent images has obtained better performance than other two methods.

关键词： Tuberculosis bacteria Fluorescent microscopy Random Forest image processing

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Fish Recognition from Low-resolution Underwater images 9

Fish Recognition from Low-resolution Underwater Images

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Sun, Xin Shi, Junyu Dong, Junyu Wang, Xinhua Ocean Univ China Coll Informat Sci & Engn Qingdao Peoples R China Changchun Inst Opt State Key Lab Appl Opt Changchun Peoples R China

ISBN: (纸本)9781509037100

The limited underwater observation scenarios pose great challenges to the problem of object recognition from the low-resolution underwater images. This paper proposes a framework to explicitly learn the discriminative features from relatively low resolution images, by resorting to deep learning approaches and super-resolution method. Firstly, the framework tackles the problem of limited discriminative information of low resolution images by a single-image super resolution method. Then state-of-the-art deep learning approaches are employed to learn recognition models for the special underwater fish recognition task. The proposed framework can be effectively implemented for real-time underwater object recognition on autonomous underwater vehicles. To verify the effectiveness of our method, experiments on a public underwater image dataset of fishes are carried out. The results show that our framework achieves promising results for fish recognition on underwater image datasets.

关键词： Deep learning image recognition underwater image super-resolution

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Soft Computing Applications: Proceedings of the 7th international Workshop Soft Computing Applications (SOFA 2016), Volume 2

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2017年

作者： Valentina Emilia Balas Lakhmi C Jain Marius Mircea Balas

ISBN: (纸本)9783319625232

These two volumes constitute the Proceedings of the 7th international Workshop on Soft Computing Applications (SOFA 2016), held on 2426 August 2016 in Arad, Romania. This edition was organized by Aurel Vlaicu University of Arad, Romania, University of Belgrade, Serbia, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control engineering and Technical informatics (SRAIT) - Arad Section, General Association of Engineers in Romania - Arad Section, and BTM Resources Arad. The soft computing concept was introduced by Lotfi Zadeh in 1991 and serves to highlight the emergence of computing methodologies in which the accent is on exploiting the tolerance for imprecision and uncertainty to achieve tractability, robustness and lower costs. Soft computing facilitates the combined use of fuzzy logic, neurocomputing, evolutionary computing and probabilistic computing, leading to the concept of hybrid intelligent systems. The rapid emergence of new tools and applications calls for a synergy of scientific and technological disciplines in order to reveal the great potential of soft computing in all domains. The conference papers included in these proceedings, published post-conference, were grouped into the following areas of research: Methods and Applications in Electrical engineering Knowledge-Based Technologies for Web Applications, Cloud Computing, Security Algorithms and Computer Networks biomedical Applications image, Text and signal processing Machine Learning and Applications Business Process Management Fuzzy Applications, Theory and Fuzzy Control Computational Intelligence in Education Soft Computing & Fuzzy Logic in Biometrics (SCFLB) Soft Computing Algorithms Applied in Economy, Industry and Communication Technology Modelling and Applications in Textiles The book helps to disseminate advances in selected active research directions in the field of soft computing, along with current issues

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Design and Development of Multi-wavelet image Fusion System Based on RF5 Framework 9

Design and Development of Multi-wavelet Image Fusion System ...

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Wang, Zhihui Xu, Gefei Lv, Yue Wu, Xudong Wang, Minjun Du, Li Inner Mongolia Univ Coll Elect Informat & Engn Hohhot Peoples R China Beijing Univ Posts & Telecommun Coll Informat & Telecommun Dept Informat & Telecommun Beijing Peoples R China

ISBN: (纸本)9781509037100

In order to overcome some shortcomings of realizing image processing using traditional DSP programming, such as long development time, low efficiency, complex, not universal system, irregularities and other issues, this paper puts forward a solution of taking TMS320DM642's TI chip as the development platform and adopting RF5 (Reference Framework 5) to realize multi-wavelet image fusion. Through this solution, we can load, fuse, and display the images that have been registered and transformed by multi-wavelet. The authors comprehensively utilize Matlab/Simulink software, CCS4.0 (embedded software tools, connection) platform, to achieve the design and development of DSP multi-wavelet image fusion system by means of automatically generating code. We implemented the fusion algorithm according to the standard of TMS320DSP algorithm and RF5, so as to realize the standardization of algorithm and software interface, which can reduce system integration tasks, shorten the development cycle, make expansion more convenient and easier.

关键词： image fusion multi-wavelet DSP reference framework 5 automatically generating code

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