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16th International Learning and Technology conference, L and T 2019

作者： Marghalani, Bashayer Fouad Arif, Muhammad Computer Science and Engineering Department College of Computer and Information Systems Umm Al-Qura University Makkah Saudi Arabia

Computer vision (CV) and image processing techniques aim at the fast development of medical images diagnoses field. As the specialist takes a long time to diagnose one MRI images, CV techniques and machine learning algorithms make the process faster than the manual way, and these techniques save time and effort. In this paper, we developed an intelligent manner for the detection and classification of brain pathologies like tumors, Alzheimer's disease (AD), or normal brain images. The proposed algorithm encompasses 4 stages: Magnetic Resonance Imaging (MRI) image acquisition, pre-processing, feature extraction, and classification. In this paper, the Bag of Features module has been used for the classification of the MRI of brain with tumor and MRI of brain of Alzheimer's disease patients from normal brain MRI. Average classification accuracy of 97% is achieved for all three classes. © 2019 The Authors. Published by Elsevier B.V.

关键词： Magnetic resonance imaging

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Batch Target Recognition Count under Complex Conditions Based on Att-Unet

Batch Target Recognition Count under Complex Conditions Base...

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International conference on Computers, Communications, and systems (ICCCS)

作者： PengPeng Jiang Kun Zhang Peijian Zhang Ping Lu Department of electrical engineering Nantong University Nantong China

ISBN: (数字)9781728161365

ISBN: (纸本)9781728161372

As we all know, the large number of counts is a challenging and time consuming task subject because of oversized number and complex conditions. However, the development of deep learning makes deep learning models very competitive in image segmentation. In this paper, we take cigarette filter rods as the research object. we first evaluate the standard Unet for the filter rod target recognition to separate target and background. Secondly, we use the focal loss function instead of the traditional cross-entropy function to solve the problem of imbalance between target and background area. Thirdly, we add a self-attention module in the traditional Unet convolutional layer to enhance the convolution effect. Fourth, we propose structural element detection criteria and round tangency matching strategy based on HMM (Hidden Markov Model) for the geometric relationship of filter rod position, which further improves the accuracy of the algorithm. We used Qu's [1], Mask-R-CNN [2], FCN [3], Deep-lab-V1 [4] and this paper's algorithm to test the performance of 30000 images from the industrial site. The performance of this paper's algorithm is completely better than the performance of the above algorithm.

关键词： Hidden Markov models Matched filters Training Deep learning Filtering algorithms Signal processing algorithms Target recognition

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Feedback alfa-rooting algorithm for medical image enhancement 17

Feedback alfa-rooting algorithm for medical image enhancemen...

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17th image processing: algorithms and systems conference, IPAS 2019

作者： Voronin, V. Zelensky, A. Agaian, S. Don State Technical University Lab. «Mathematical Methods of Image Processing and Computer Vision Intelligent Systems» Gagarina 1 Rostov on Don Russia Moscow State University of Technology "STANKIN" Moscow Russia CUNY/ College of Staten Island Dept. of Computer Science New York United States

This paper presents a new combined local and global transform domain-based feedback image enhancement algorithm for medical diagnosis, treatment, and clinical research. The basic idea in using local alfa-rooting method is to apply it to different disjoint blocks with different sizes. The block size and alfa-rooting parameters driven through optimization using the Agaian's cost function (image enhancement non-reference quality measure). The presented new approach allows enhancing MRI and CT images with uneven lighting and brightness gradient by preserving the local image features/details. Extensive computer simulations (CS) on real medical images are offered to gage the presented method. CS shows that our method improves the contrast and enhances the details of the medical images effectively compared with the current state-of-art methods. © 2019, Society for Imaging Science and Technology.

关键词： Clinical research

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Design of Active visual Marker for High Speed Object Tracking by Frame Subsampling 27

Design of Active Visual Marker for High Speed Object Trackin...

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27th International conference on Information, Communication and Automation Technologies (ICAT)

作者： Kreho, Adnan Hadzajlic, Jasmin Sokic, Emir Univ Sarajevo Dept Automat Control & Elect Fac Elect Engn Sarajevo Bosnia & Herceg

ISBN: (纸本)9781728145433

The trajectory of a moving object may be extracted from video using image processing algorithms. However, the quality of the extracted information largely depends on the frame rate and exposure time of the camera, thus it is difficult to capture fast movement using slower and less expensive cameras. To this end, we propose to use an active modulated light source for object tracking, interacting with exposure times and sub-sampling existing frames. A prototype of a multi-functional active visual marker is presented in this paper. The system is based on the ESP-WROOM-32 microcontroller, which is configured to use various communication protocols, namely WiFi 802.11, RF 2.4 GHz GFSK and RS485. The microcontroller controls the RGB LED, which is used as light source. In addition, the system can be synchronized with the external real-time clock. The experimental results have illustrated the advantages and disadvantages of the designed active markers and pointed out the directions for future work and development.

关键词： Object tracking active marker frame subsampiing embedded systems

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Fast Fractional Motion Estimation Hardware Design of Inter Predication for AVS2

Fast Fractional Motion Estimation Hardware Design of Inter P...

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IEEE International conference on Signal and image processing (ICSIP)

作者： Rongbing Yang Yu Hong Guoqing Xiang Kaiyang Liu Wei Yan School of Software and Microelectronics Peking University School of Electronics Engineering and Computer Science Peking University Beijing China

ISBN: (数字)9781728168968

ISBN: (纸本)9781728168975

Fractional Motion Estimation (FME) is a very significant part of video coding technology, but its high computational complexity often limits the real-time performance and makes the area cost very high in hardware design. In this brief, this paper puts forward some novel joint optimizations with taking both algorithm and architecture into account to increase the throughput and reduce the area cost as much as possible, including SATD-based inter coding unit (CU) early split method and pipeline the 25 points parallel search and interpolation. In addition, to further improve throughput, for CUs with size greater than 8×8, we adopt the method of splicing to further reduce redundant operations and improve the ability of architecture reuse. These ideas help us save nearly 75% of the computational effort and complexity in FME of inter frame prediction. Finally, verified by the Xilinx vivado HLS, the experiment results show that the algorithms and architecture proposed in this paper are able to process videos of 1920×1080@60 fps under the 300 MHz clock frequency with 3% bitrates increase in average.

关键词： video coding Interpolation Motion estimation Computer architecture Throughput Hardware Real-time systems

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Research on New Stereo Matching Algorithm of Multi-Rotor UAV Based on vision 17

Research on New Stereo Matching Algorithm of Multi-Rotor UAV...

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17th International conference on Manufacturing Research, ICMR 2019, incorporating the 34th National conference on Manufacturing Research, NCMR 2019

作者： Wang, Haixin Jin, Yan Shen, Jianxin College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China School of Mechanical and Aerospace Engineering Queen's University Belfast Belfast United Kingdom

ISBN: (纸本)9781643680088

The application of multi-rotor UAV in vision has been developed rapidly in recent years, and multi-rotor unmanned aerial vehicles (UAV) can't be widely used without the aid of a visual system. The application of visual technology in UAV has attracted more and more attention with the continuous development of image processing and environment reconstruction technology. Getting accurate depth map from the stereo image has always been the pursuit of researchers. Stereo matching is the most important part of stereo vision. An improved matching algorithm is proposed to solve the problems of high image noise and low image accuracy in binocular vision imaging of multi-rotor UAV after binocular information fusion. Experimental results show that the proposed algorithm has advantages in accuracy compared with other algorithms. The validity and reliability of the proposed stereo matching algorithm for multi-rotor UAV based on binocular vision are verified by indoor simulation tests and real environment tests of a UAV. © 2019 The authors and IOS Press. All rights reserved.

关键词： Stereo image processing

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Autonomous path guiding robot for visually impaired people

Autonomous path guiding robot for visually impaired people

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International conference on Cognitive Informatics and Soft Computing, CISC 2017

作者： Megalingam, Rajesh Kannan vishnu, Souraj Sasikumar, vishnu Sreekumar, Sajikumar Department of Electronics and Communication Engineering Amrita University Amritapuri India

ISBN: (纸本)9789811306167

This paper introduces an intelligent and efficient path guidance robot to assist the visually impaired people in their movements. This is a novel device for the replacement of strenuous guide dogs. The robot has the capability to move along multiple paths and then remember as well as retrace all of them, thus making it a perfect substitute for a guide dog which is often a luxury for the ninety percent of blind people living in low income settings. The robot is capable to guide the user to travel places which cannot be traced using GPS. Since most of the navigation systems that are developed so far for the blind people employ a complex conjunction of positioning systems, video cameras, location mapping and image processing algorithms, we have designed an affordable low-cost prototype navigation system which serves the purpose of guiding the visually impaired people both in indoor as well as outdoor environment. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Navigation systems

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Interactive volumetric segmentation for textile micro-tomography data using wavelets and nonlocal means

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STATISTICAL ANALYSIS AND DATA MINING 2019年第4期12卷 338-353页

作者： MacNeil, J. Michael L. Ushizima, Daniela M. Panerai, Francesco Mansour, Nagi N. Barnard, Harold S. Parkinson, Dilworth Y. Lawrence Berkeley Natl Lab Computat Res Div CAMERA 1 Cyclotron RdBldg 59Off 3017 Berkeley CA 94720 USA Univ Calif Berkeley Berkeley Inst Data Sci Berkeley CA 94720 USA NASA Ames Res Ctr AMA Inc Moffett Field CA 94035 USA NASA Ames Res Ctr Adv Supercomp Div Moffett Field CA 94035 USA LBNL Adv Light Source CAMERA Berkeley CA USA

This work addresses segmentation of volumetric images of woven carbon fiber textiles from micro-tomography data. We propose a semi-supervised algorithm to classify carbon fibers that requires sparse input as opposed to completely labeled images. The main contributions are: (a) design of effective discriminative classifiers, for three-dimensional textile samples, trained on wavelet features for segmentation;(b) coupling of previous step with nonlocal means as simple, efficient alternative to the Potts model;and (c) demonstration of reuse of classifier to diverse samples containing similar content. We evaluate our work by curating test sets of voxels in the absence of a complete ground truth mask. The algorithm obtains an average 0.95 F1 score on test sets and average F1 score of 0.93 on new samples. We conclude with discussion of failure cases and propose future directions toward analysis of spatiotemporal high-resolution micro-tomography images.

关键词： 3D image processing 3D segmentation 3D woven carbon fiber composites machine learning microCT neural networks

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An image Thresholding Method Based on Differential Evolution Algorithm and Genetic Algorithm 10

An Image Thresholding Method Based on Differential Evolution...

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10th IEEE International conference on Intelligent Data Acquisition and Advanced Computing systems - Technology and Applications (IDAACS)

作者： Ye, Zhiwei Zhang, Aixin Cao, Ye Ma, Lie Jin, Can Hu, Xiang Hu, Jiwei Hubei Univ Technol Wuhan Hubei Peoples R China Wuhan Jizhi Technol Co LTD Wuhan Hubei Peoples R China Wuhan Fiberhome Tech Serv Co Ltd Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9781728140681

Thresholding is the simplest but most effecttive segmentation technique for image analysis. However, the computational complexity increases exponentially with the increase of threshold number in order to seek the most appropriate threshold values. Therefore, stochastic optimization algorithm are often used to overcome excessive computational problems, but the single optimization algorithm often falls into the local optimum. In general, hybrid algorithm is able to produce better performance. As a result, a parallel coupled mode(DE_GA in brief) of differential evolution algorithm (DE) and genetic algorithm (GA) is proposed for solving multi-threshold problem and The maximum variance is used as the fitness function. The experimental result displays that compared with a single algorithm, the results of the hybrid algorithm are relatively stable, which means that the parallel coupled DE_GA algorithm combined with Otsu might be an effect and practical image segmentation method.

关键词： Parallel coupled mode Genetic algorithms Differential Evolution Algorithm image segmentation, Thresholding

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Crystal Lattice Parametric Identification Based on Analysis of Isosurface Configurations

Crystal Lattice Parametric Identification Based on Analysis ...

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Information Technology and Nanotechnology (ITNT), International conference on

作者： Dmitriy Kirsh Image Processing Systems Institute of RAS - Branch of the FSRC "Crystallography and Photonics" RAS Samara National Research University Samara Russia

ISBN: (数字)9781728170411

ISBN: (纸本)9781728170428

The paper deals with the approach to crystal lattice identification based on analysis of isosurface configurations. This method allows to estimate the relative positioning of nodes inside a unit cell, which, theoretically, should provide favorable conditions for the creation of identification algorithms resistant to structure distortions. The major problem of high computational complexity is solved by modifying the method using the three-dimensional periodicity of crystal lattice structures. The study of the method performed on a large base of reference lattices has confirmed its high resistance to structure distortions. In addition, the joint analysis of isosurface configurations and parameters of Bravais unit cells allowed to increase the accuracy of structural identification by an average of 13%.

关键词： Resistance Lattices Crystals Distortion Computational complexity Isosurfaces Periodic structures

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