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2nd international conference on Intelligent Computing and Communication, ICICC 2017

2nd International Conference on Intelligent Computing and Co...

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2nd international conference on Intelligent Computing and Communication, ICICC 2017

ISBN: (纸本)9789811072444

The proceedings contain 71 papers. The special focus in this conference is on Intelligent Computing and Communication. The topics include: vision-based target tracking intelligent robot using NI myRIO with LabVIEW;detection of misbehaviors nodes in wireless network with help of pool manager;evaluation of multi-label classifiers in various domains using decision tree;an effective multilabel classification using feature selection;High-performance pipelined FFT processor based on radix-22for OFDM applications;an image processing approach to blood spatter source reconstruction;overlapping character recognition for handwritten text using discriminant hidden semi-markov model;a literature survey on authentication using behavioural biometric techniques;number system oriented text steganography in English language for short messages: A decimal approach;Validation of open core protocol by exploiting design framework using system verilog and UVM;novel robust design for reversible code converters and binary incrementer with quantum-dot cellular automata;routing with secure alternate path selection for limiting the sink relocation and enhanced network lifetime;gene presence and absence in genomic big data for precision medicine;a survey on service discovery mechanism;analysis of multiple features and classifier techniques combination for image pattern recognition;smart and precision polyhouse farming using visible light communication and internet of things;Acceleration of CNN-based facial emotion detection using NVIDIA GPU;research issues for energy-efficient cloud computing;Implementation of REST API automation for interaction center;predictive analysis of e-commerce products;cellular automata logic block observer based testing for network-on-chip architecture;user privacy and empowerment: Trends, challenges, and opportunities;Evolution metrics for a BPEL process.

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Machine vision Based Yak Body Size Measuring Points 2

Machine Vision Based Yak Body Size Measuring Points

引用

2018 2nd Annual international conference on Cloud Technology and Communication Engineering, CTCE 2018

作者： Sun, Zijie Zhang, Chen Qin, Xiaofeng Zhang, Yu-An Du, Meiyun Song, Weiru Song, Rende Department of Computer Technology and Applications University of Qinghai Xining810016 China Interdisciplinary Graduate School of Agriculture and Engineering University of Miyazaki Japan Yushu Prefecture Animal Husbandry and Veterinary Station Yushu Qinghai815000 China

In livestock breeding, it is a research hotspot to conduct non-contact measuring and acquire the body size parameters of animals without stirring stress. And traditional animal body size manual measurement methods involve heavy workload and safety risks. This paper aims to acquire the color image of yak by shooting the traditional body size measurement position of yaks in Sanjiangyuan area. Then, a classification processing based foreground extraction method is used to extract the yak from the image;after the profile curve of the yak is extracted, the temple point and ischium end of the yak are obtained by means of calculating the distance between the image border and the central point. Finally, the body height and body dip length points of the yak are acquired. This paper specially extracts the yak in a yak image shot in Sanjiangyuan area, Qinghai Province, marks points and displays them. The experiment suggests that the dark yak body size point marking algorithm studied by this paper is quite effective to point marking of two-dimensional yak images. © Published under licence by IOP Publishing Ltd.

关键词： Animals

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Clustering analysis based on segmented images 2nd

Clustering analysis based on segmented images

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2nd international conference on Machine Learning and Intelligent Communications, MLICOM 2017

作者： Zheng, Hongxu Wang, Jianlun He, Can College of Information and Electrical Engineering China Agricultural University Beijing100083 China

ISBN: (纸本)9783319735634

image segmentation plays an important role in the field of digital production management. image resolution is an important factor affecting the size of its segmentation and segmentation efficiency, and the physical characteristics of the image capturing device is another important factor. With high-resolution segmentation algorithm in image segmentation, we often find that the edge contour image segmentation is difficult to accurately determine, more complex image arithmetic operation efficiency is not high and images taken with a different device in response to segmentation algorithms are very different. In this paper, the plant leaf image collected from different cameras was used as the object of study, and the feature quantity was extracted. The appropriate segmentation boundary was determined by cluster analysis. The leaf image was pretreated with the resolution adjustment, and the leaf image was in the appropriate segmentation feature range. After the clustering domain processing of the feature range in this paper, it solves the problem that the real edge of the leaf area information is too difficult to distinguish, and effectively solves the problem of complex image algorithm and ordinary pc machine in the process of complex image processing Efficiency issues. The appropriate segmentation feature range of the devices is established for different devices, which effectively solves the different response of different devices to the segmentation algorithm. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2018.

关键词： image resolution

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Night Time image Enhancement by Improved Nonlinear Model 2nd

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2nd international conference on Machine Learning and Intelligent Communications, MLICOM 2017

作者： Zhang, Yao Wang, Chenxu Wang, Xinsheng Wang, Jing Man, Le Information and Electrical Engineering School Harbin Institute of Technology Harbin China

ISBN: (纸本)9783319734460

Low light or poor shooting angle and other issues often make the camera to take night time images and affect the naked-eye observation or computer identification, so it is important to enhance the lightness of night time image. Although the existing non-linear luminance enhancement method can improve the brightness of the low light area, the excessive promotion led to high light area distortion. Based on the existing image luminance processing algorithm, we proposed an adaptive night time image improving method in the basis of nonlinear brightness enhancement model is proposed to process the segmentations of image brightness by using the logarithmic function. The segmentation threshold is determined by the Otsu, and the adjustment factor of the backlight region in the transfer function is calculated from the area ratio of the backlight area. The conclusion comes from the simulation. The method involves improving the image quality and ensuring that the entire picture is natural without distortion. In the meanwhile, the processing speed is not much slower compared with the existing processing algorithms. © 2018, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Luminance

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Detection of RPE Region: Non-separated Inner and Outer Hyper-reflective Layer Using Neighbouring Pixel Connectivity Paradigm

Detection of RPE Region: Non-separated Inner and Outer Hyper...

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2nd international conference on Recent Advancement in computer, Communication and Computational Sciences (RACCCS)

作者： Mishra, Piyush Bhatnagar, Charul GLA Univ Dept CEA Mathura 281406 India

ISBN: (纸本)9789811073861;9789811073854

The retina is composed of ten layers, with the retinal pigment epithelium (RPE) being the outermost layer tightly attached to the choroid. With the increased knowledge about the various functions performed by the RPE, the ophthalmologists have a better understanding of the various diseases leading to blindness. In this work, we propose a method to identify RPE region in optical coherence tomography (OCT) visualization of the retina. This paper focuses on detection of RPE region, the non-separated region between the inner and outer hyper-reflective layer (HRL). The proposed method comprises a bilateral filter for speckle de-noising while maintaining layer boundaries. Detection of inner HRL is a prominent research dimension having significant correlation with the human visual acuity. The proposed work validation is done with the ground truths (manually delineated by an expert panel). Evaluation of the proposed method is done on 220 images from 23 patients at different orientation styles with 90.45% correct detections.

关键词： Bio-medical imaging computer-aided diagnosis Optical coherence tomography Retinal image processing Retinal pigment epithelium

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2nd international conference on Information and Communication Technology for Intelligent Systems, ICTIS 2017

2nd International Conference on Information and Communicatio...

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2nd international conference on Information and Communication Technology for Intelligent Systems, ICTIS 2017

ISBN: (纸本)9783319636443

The proceedings contain 147 papers. The special focus in this conference is on Information and Communication Technology for Intelligent Systems. The topics include: Design of high-speed LVDS data communication link using FPGA;face super resolution by tangential and exponential kernel weighted regression model;monitoring of distributed resources based on client-server (single-hop) mobile agents in homogeneous network of interconnected nodes;energy balanced clustering protocol using particle swarm optimization for wireless sensor networks;routing protocol for device-to-device communication in softnet towards 5G;a survey of computer vision based corrosion detection approaches;word sense ambiguity in question sentence translation;implementing a hybrid crypto-coding algorithm for an image on FPGA;realization of FPGA based PID controller for speed control of DC motor using xilinx sysgen;emerging trends in ADR;natural language interface for multilingual database;a simple and efficient text-based CAPTCHA verification scheme using virtual keyboard;outcome fusion-based approaches for user-based and item-based collaborative filtering;a practical perspective;financial time series clustering;financial time series clustering;challenges and research issues;simplified process of obstructive sleep apnea detection using ECG signal based analysis with data flow programming;smart two level k-means algorithm to generate dynamic user pattern cluster;notification of data congestion intimation [ndCI] for IEEE 802.11 adhoc network with power save mode;a case study on level control system and deep neural network based classification of tumourous and non-tumorous medical images.

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Virtual Wardrobe For Physically Impaired Using Microsoft Kinect Sensor 2

Virtual Wardrobe For Physically Impaired Using Microsoft Kin...

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2nd IEEE international conference on Signal and image processing (ICSIP)

作者： Hamid, Md. Farhan Alam, Md. Ashraful BRAC Univ Dept CSE Dhaka Bangladesh

ISBN: (纸本)9781538609699

This research intends to solve the virtual wardrobe problem for physically impaired. It is difficult for the physically impaired to try out outfits by themselves in a trial room. It is far more convenient for them to try the outfits virtually. To best of our knowledge, there is no such system for the physically disabled. Our approach is to solve this problem using head gestures and voice commands. We intend to solve this problem using Kinect Head Tracking and Voice Recognition features. Pitching their heads right or left, they can navigate through the items and blinking allows to select. The system will be designed with friendly interface, simple process and easy operations for the physically impaired to use with ease.

关键词： microsoft kinect image processing computer vision physically impaired virtual wardrobe

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Visual Pedestrian Tracking from a UAV Platform 2

Visual Pedestrian Tracking from a UAV Platform

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2nd international conference on Multimedia and image processing (ICMIP)

作者： Zhang, Li Zhang, Zenghui Xiong, Huilin Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China

ISBN: (纸本)9781509059546

Visual tracking is a challenging problem in computer vision, especially when the camera platform is moving. To track a target pedestrian from a UAV (Unmanned Aerial Vehicle) mobile platform, multiple techniques, such as motion control of UAV, visual detection and tracking are needed. This study presents a new tracking method, which mainly involves object tracking, pedestrian detection and online color feature matching. The algorithm of the proposed method has two main components: a median flow tracker and a pedestrian detection which is based on fast feature pyramids. The proposed tracking method is thoroughly evaluated on various public videos and real scene videos from UAV cameras, and compared with existing state-of-the-art tracking methods to show its effectiveness.

关键词： UAV platform pedestrian tracking color feature vision detection

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Lorentzian Norm Based Super-Resolution Reconstruction of Brain MRI image 2nd

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2nd international conference on Machine Learning and Intelligent Communications, MLICOM 2017

作者： Bao, Dongxing Li, Xiaoming Li, Jin College of Automation Harbin Engineering University Harbin150001 China School of Electronic Engineering Heilongjiang University Harbin150080 China Department of Microelectronics Science and Technology Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9783319734460

Nowadays, SRR (super resolution image reconstruction) technology is a very effective method in improving spatial resolution of images and obtaining high-definition images. The SRR approach is an image late processing method that does not require any improvement in the hardware of the imaging system. In the SRR reconstruction model, it is the key point of the research to choose a proper cost function to achieve good reconstruction effect. In this paper, based on a lot of research, Lorenzian norm is employed as the error term, Tikhonov regularization is employed as the regularization term in the reconstruction model, and iteration method is employed in the process of SRR. In this way, the outliers and image edge preserving problems in SRR reconstruction process can be effectively solved and a good reconstruction effect can be achieved. A low resolution MRI brain image sequence with motion blur and several noises are used to test the SRR reconstruction algorithm in this paper and the reconstruction results of SRR reconstruction algorithm based on L2 norm are also be used for comparison and analysis. Results from experiments show that the SRR algorithm in this paper has better practicability and effectiveness. © 2018, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Cost functions

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A Multi-frame image Speckle Denoising Method Based on Compressed Sensing Using Tensor Model 2nd

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2nd international conference on Machine Learning and Intelligent Communications, MLICOM 2017

作者： Zhou, Ruofei Wang, Gang Yang, Wenchao Li, Zhen Xu, Yao Harbin Institute of Technology Harbin China

ISBN: (纸本)9783319734460

Due to the bad channel environment and poor image sampling equipment, images are often contaminated by noise in the process of collection, transmission and processing. Speckle noise, which is difficult and complex to eliminate, is one of the common noise appearing in image processing. Denoising methods based on Compressed Sensing (CS) technology have been proved as useful tools in suppressing speckle noise of single-frame images. However, temporal correlation in multi-frame images has not yet been utilized. Considering that the traditional denoising methods do not work satisfactorily in speckle noise reduction, a multi-frame image speckle denoising methods based on compressed sensing using tensor model is proposed. The first step is to use the third-order tensor to represent the blocks of image sequences, then the denoising tensor model is established according to the CS theory and the corresponding optimization problem is raised. The problem is divided into three parts: the sparse representation, the tensor dictionary update and the image reconstruction. A Kruskal tensor-based Orthogonal Matching Pursuit (OMP) and Candecomp/Parafac (CP) analysis are used to solve these problems and get the denoised image. At last, simulations are conducted to compare the CS method and traditional methods. It is shown that the CS-based multi-frame speckle denoising method performs well in noise variance and can significantly enhance the visual quality of the image. © 2018, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Compressed sensing

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