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检索条件"任意字段=3rd International Conference on Computer Vision and Image Processing, CVIP 2018"

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Using Off-Line Handwriting to Predict Blood Pressure Level: A Neural-Network-Based Approach 3rd

Using Off-Line Handwriting to Predict Blood Pressure Level: ...

引用

3rd EAI international conference on Future Access Enablers of Ubiquitous and Intelligent Infrastructures (Fabulous)

作者： Gavrilescu, Mihai Vizireanu, Nicolae Univ Politehn Bucuresti Dept Telecommun 1-3 Iuliu Maniu Blvd Bucharest 061071 6 Romania

ISBN: (纸本)9783319922133;9783319922126

We propose a novel, non-invasive, neural-network based, three-layered architecture for determining blood pressure levels of individuals solely based on their handwriting. We employ four handwriting features (baseline, lowercase letter "f", connecting strokes, writing pressure) and the result is computed as low, normal or high blood pressure. We create our own database to correlate handwriting with blood pressure levels and we show that it is important to use a predefined text for the handwritten sample used for training the system in order to have high prediction accuracy, while for further tests any random text can be used, keeping the accuracy at similar levels. We obtained over 84% accuracy in intra-subject tests and over 78% accuracy in inter-subject tests. We also show there is a link between several handwriting features and blood pressure level prediction with high accuracy which can be further exploited to improve the accuracy of the proposed approach.

关键词： Neural networks E-health Bioengineering image processing

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Neural Network Based Architecture for Fatigue Detection Based on the Facial Action Coding System 3rd

Neural Network Based Architecture for Fatigue Detection Base...

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3rd EAI international conference on Future Access Enablers of Ubiquitous and Intelligent Infrastructures (Fabulous)

作者： Gavrilescu, Mihai Vizireanu, Nicolae Univ Politehn Bucuresti Dept Telecommun 1-3 Iuliu Maniu Blvd Bucharest 06107 6 Romania

ISBN: (纸本)9783319922133;9783319922126

We present a novel non-invasive neural network based three layered system for detecting fatigue by analyzing facial expressions evaluated using the Facial Action Coding System. We analyze 16 Action Units pertaining to eye and mouth regions of the face. We define an Action Units map containing Action Unit intensity levels for each frame in the video sequence and we analyze this map in a pattern recognition task via a feed-forward neural network. We show that emotion-induced frontal face recordings offer more information in the training stage, while for testing stage the random dataset can be used with no major impact on accuracy, specificity and sensitivity. We obtain over 88% accuracy in intra-subject tests and over 83% for inter-subject tests and we show that our system surpasses the state-of-the-art in terms of accuracy, specificity, sensitivity and response time.

关键词： Neural networks e-health Bioengineering Facial expression recognition image processing

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Color image segmentation of disease infected plant images captured in an uncontrolled environment 3rd

Color image segmentation of disease infected plant images ca...

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3rd international conference on Next Generation Computing Technologies, NGCT 2017

作者： Verma, Toran Dubey, Sipi Sabrol, Hiteshwari Rungta College of Engineering and Technology CSVTU BhilaiCG490024 India DAV University JalandharPunjab144012 India

ISBN: (纸本)9789811086595

In the field of an automated vision system for integrated disease control in plants, accurate identification of plant diseases is very important. The symptoms of the occurrences of diseases appear in different parts of the plant. The analysis of segmented images of infected parts in plant images helps to take curative and/or corrective measures for the diseases. In this paper, we present a threshold-based segmentation using RGB-L*a*b* hybrid color space features to segment the plant diseases from the digitally acquired images. In this proposed method, without interfering with spatial features of the color image, the quantization and binarization had been done in L*a*b* color space image and it applied to RGB color image for the segmentation of the image. Initially, the acquired RGB color images had been transformed into L*a*b* color images. Then multilevel threshold had been applied on the a* component of L*a*b* image. On the basis of threshold value a*, components of a* had been quantized, and equivalent binary matrices had been created. These binary matrices had been applied individually to the R, G, and B components of RGB images separately and concatenated to perform color image segmentation of infected part of the disease in the plant image. Our calculation gives the prominent result to segment diseased part of the plant images captured in an uncontrolled environment. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Disease control

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NCC Feature Matching Optimized Algorithm Based on Constraint Fusion

NCC Feature Matching Optimized Algorithm Based on Constraint...

引用

international conference on image, vision and Computing (ICIVC)

作者： Jin Sun Yuan Liu Yu Ding Xinglong Zhu Juntong Xi College of Mechanical Engineering Yangzhou University Yangzhou Jiang Su P.R. China

ISBN: (纸本)9781538649923

In this paper, a binocular stereo vision three-dimensional (3D) reconstruction algorithm is proposed. In order to reduce the computation in feature extraction process, it begins with selecting candidate corner points, and then uses this as the center to establish the search area. Finally, scale invariant feature transform (SIFT) algorithm is used to extract corner points. In the process of stereo matching, the rough matching point pairs obtained from the Normal Cross Correlation (NCC) algorithm are applied to feature constraints to get the precise matching point pairs so that the final experiment realizes the 3D reconstruction of objects.

关键词： Feature extraction Cameras Three-dimensional displays image reconstruction Microsoft Windows Signal processing algorithms Face

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Single Foggy image Restoration Under Hardy Space

Single Foggy Image Restoration Under Hardy Space

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international conference on image, vision and Computing (ICIVC)

作者： Shiping Wang Kun Liu Duyan Bi Linyuan He Chen Wang Shiping Ma Shan Gao Air Force Engineering Univ. The School of Aeronautics and Astronautics Engineering Baqiao District Xi'an

ISBN: (纸本)9781538649923

The foggy image recovery is one of hot topics in the image processing. Considering that the haze images fade the colors and reduce the contrast in the process of defogging, in this paper, we propose a novel regularization method of image defogging based on Hardy space transformation. Our method uses model analysis and mathematical derivation to use the transformed pseudo-differential operator, which obtains more statistical features and defines the extent of image defogging. The effective comparison algorithm is preferred. Extensive quantitative and qualitative evaluations have been demonstrated that our algorithm improves effectively the defogging of real and simulated images.

关键词： image edge detection Atmospheric modeling Attenuation image restoration Scattering Mathematical model Degradation

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License Plate image Super-Resolution Based on Convolutional Neural Network

License Plate Image Super-Resolution Based on Convolutional ...

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international conference on image, vision and Computing (ICIVC)

作者： Yang Yang Ping Bi Ying Liu Center for Image and Information Processing Xi'an University of Posts and Telecommunications Xi'an China

ISBN: (纸本)9781538649923

To improve the visual quality of the low-resolution license plate image in the video surveillance system, this paper proposes a new method of super-resolution, namely multi-scale super-resolution convolutional neural network (MSRCNN), it was inspired by Inception architecture of GoogLeNet. The proposed method uses different sizes of filters for parallel convolution to obtain different features of the low-resolution license plate image, then the features can be fused by the layer of concatenation. Finally, the high-resolution images can be reconstructed through non-linear mapping. Experimental results prove that the proposed method can improve the quality of low-resolution license plate image obviously.

关键词： image reconstruction Licenses image resolution Training Feature extraction Testing Convolutional neural networks

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Overview of Artifacts Detection and Elimination Methods for BCI Using EEG

Overview of Artifacts Detection and Elimination Methods for ...

引用

international conference on image, vision and Computing (ICIVC)

作者： Clifford Maswanganyi Chunling Tu Pius Owolawi Shengzhi Du Department of Computer Systems Engineering Tshwane University of Technology Pretoria Gauteng RSA Department of Electrical Engineering Tshwane University of Technology Pretoria Gauteng RSA

ISBN: (纸本)9781538649923

Electroencephalogram (EEG) is the most commonly utilized method of mapping brain wave patterns from the scalp. It is a process of extracting electrical activities of the brain in the form of EEG signals using non-invasive methods. In EEG based techniques, a challenge exists in the form of signal contamination caused by internal and external factors in the recorded EEG signals., such as the artifacts, interferences among multiple EEG sources, and noise. Signal pre-processing is the most significant phase for EEG based applications, for instance, the brain computer interface (BCI) systems. This is because the quality of data acquired from the brain through EEG measurements is dependent on the effectiveness of artifact detection and removal methods. During EEG recording there are several factors that influence the quality of data. One of the factors of signal contamination occurs as the result of physiological and non-physiological artifacts. To detect and remove such contaminations from EEG signals, there are several efficient artifact detection and elimination techniques based on certain pre-processing methods. The main objective of this study is to demonstrate various types of artifacts in EEG recordings as results of external and internal factors. Furthermore, the study will also present an extensive review of existing artifacts identification and elimination methods applied on EEG signals.

关键词： Electroencephalography Physiology Discrete wavelet transforms Electrodes Contamination Electric potential

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Understanding indoor scene: Spatial layout estimation, scene classification, and object detection 18

Understanding indoor scene: Spatial layout estimation, scene...

引用

3rd international conference on Multimedia Systems and Signal processing, ICMSSP 2018

作者： Ismail, A.S. Seifelnasr, M.M. Guo, Hongxing Huazhong University of Science and Technology China Zagazig University Zagazig44519 Egypt Helwan University Cairo11792 Egypt School of Computer Science and Technology Huazhong University of Scienc and Technology China

ISBN: (纸本)9781450364577

In this paper, we seek to understand scene from different viewpoints such as estimating the spatial layout of indoor scenes, detecting objects in the scene and making scene classification. In the previous work, every step has been done in a separate process so in this work we combine the three steps in one algorithm. To understand the indoor scene this requires interpreting the estimation of multiple scene elements and studying the relation between them. We propose a method that takes a single indoor image and then the relation between scene elements can be automatically learned and applied to totally understand the indoor scenes. Our proposed method consists of two steps: the first step is estimating the spatial layout of indoor scenes and this is done by extracting line segments and estimating the three orthogonal vanishing points. The orientation of the surfaces in the scene is defined by the vanishing points and so constructs the layout of the walls, ceiling, and floor. The second step is studying the relation between scene elements and this means that studying the relation between scene classification, objects in the scene, and layout estimation. We conduct extensive experiments to evaluate our proposed method performance on a single indoor image. We achieve superior accuracy results on two public datasets and provide a robust estimation of scene type, estimation of spatial layout and 3D objects. © 2018 Association for Computing Machinery.

关键词： Object detection

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Grab Cut image Segmentation Based on image Region

Grab Cut Image Segmentation Based on Image Region

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international conference on image, vision and Computing (ICIVC)

作者： Yubing Li Jinbo Zhang Peng Gao Liangcheng Jiang Ming Chen National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (纸本)9781538649923

Grab Cut algorithm is one of the most popular method in the field of image segmentation. It uses texture information and boundary information of image, and achieves good segmentation results with a small number of user interaction. But there are two significant drawbacks about this algorithm. Firstly, If the background is complex or the background and the object are very similar, the segmentation will not be very good. On the other hand, the relatively slow speed and Complex iterative process of the algorithm are greatly limited its application. In this paper, to develop these aspects, we proposed an improved grab cut algorithm. This algorithm is the combination of grab cut and graph-based image segmentation [1]. After the experiment, the improved algorithm is applied to more complex situation.

关键词： image segmentation image edge detection computer vision image color analysis Minimization Mathematical model Classification algorithms

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Partitioned Logarithmic Tone Mapping Algorithm with Detail Compensation

Partitioned Logarithmic Tone Mapping Algorithm with Detail C...

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international conference on image, vision and Computing (ICIVC)

作者： Jialin Liu Ying Liu Weihua Liu Tingge Zhu Center for Image and Information Processing Xi'an University of Posts and Telecommunications Xi'an China

ISBN: (纸本)9781538649923

We present a partitioned logarithmic tone mapping algorithm with detailed compensation. First, the High Dynamic Range (HDR) image is divided into a base layer and a detail layer. Then, different adaptive logarithmic functions are proposed for the low, medium, and high luminance regions in the base layer. At last, a pixel-level fusion algorithm is used to eliminate the boundary effect of each region. We also propose an adaptive function to adjust the detail layer. Experimental results show that our algorithm can effectively compress the dynamic range, the image details after tone mapping are more abundant and the color saturation is higher.

关键词： Partitioning algorithms Dynamic range Heuristic algorithms image coding image color analysis Mathematical model Brightness

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