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2018 2nd international conference on computer graphics and digital image processing (cgdip 2018)

Journal of Physics: conference Series 2018年第1期1098卷

PREFACE cgdip 2018 was held in Bangkok, Thailand from July 27-29, 2018. cgdip 2018 was organized by the Asia Pacific Institute of Science and Engineering (APISE). The conference provides a useful and wide platform both to display the latest research and for the exchange of research results and thoughts in computer graphics and digital image processing. The participants of the conference were from almost every part of the world, with backgrounds in either academia or industry, even well-known enterprise. The success and prosperity of the conference is reflected in the high level of the papers received. The proceedings are a compilation of the accepted papers and represent an interesting outcome of the conference. This book covers two chapters: 1. Applications & Visualization; 2. image processing, Detection and Recognition. We would like to acknowledge all of those who supported cgdip 2018. Each individual and institutional help were very important for the success of this conference. Especially we would like to thank the organizing committee for their valuable advice in the organization and helpful peer review of the papers. We sincerely hope that cgdip 2018 will be a forum for excellent discussions that will put forward new ideas and promote collaborative researches. We are sure that the proceedings will serve as an important research source of references and the knowledge, which will lead to not only scientific and engineering progress but also other new products and processes. Prof. Shahram Latifi, University of Nevada, Las Vegas, USA

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Deep Self-Integrated 3D Left Atrium Segmentation Network Based on Semi-Supervised Learning

Deep Self-Integrated 3D Left Atrium Segmentation Network Bas...

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digital image processing and computer Applications (DIPCA), international conference on

作者： Zijia Wang Juan Mo Chenfei Wang College of Automation and Electrical Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia China Key Laboratory of Synthetical Automation for Process Industries at Universities of Inner Mongolia Autonomous Region Baotou Inner Mongolia China School of Science Inner Mongolia University of Science and Technology Baotou Inner Mongolia China

ISBN: (数字)9798331534509

ISBN: (纸本)9798331534516

Pixel-accurate tissue segmentation of the left atrium (LA) can assist clinicians in diagnosing atrial fibrillation and assessing cardiac function. However, existing LA segmentation methods suffer from poor performance in complex anatomical structures due to insufficient utilization of structural information. To address this issue, we propose a Deep self-integrated Uncertainty-aware Mean Teacher network (DU-MT), which comprises a Multilevel deep melting furnace module (MDFM) and a Bifocal V-Net (BV-Net) backbone. Specifically, MDFM fuses uncertainty maps from multiple decoder levels using an entropy-weighted strategy to dynamically adjust the consistency loss. BV-Net enhances boundary continuity through spatial-channel dual-branch attention. In addition, a Vision Transformer (ViT) is integrated into the bottleneck layer of the V-Net to model long-range dependencies. Extensive experiments on the MICCAI 2018 LA Dataset demonstrate that our approach achieves better or comparable performance to state-of-the-art methods, making it suitable for real-world clinical applications.

关键词： image segmentation computer vision Uncertainty Three-dimensional displays Fuses Furnaces digital images Semisupervised learning Transformers Decoding

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2nd international conference on computer Vision and image processing, CVIP 2017

2nd International Conference on Computer Vision and Image Pr...

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2nd international conference on computer Vision and image processing, CVIP 2017

ISBN: (纸本)9789811078941

The proceedings contain 64 papers. The special focus in this conference is on . The topics include: A novel robust reversible watermarking technique based on prediction error expansion for medical images;integrated Feature Exploration for Handwritten Devanagari Numeral Recognition;Privacy Preserving for Annular Distribution Density Structure Descriptor in CBIR Using Bit-plane Randomization Encryption;near-Duplicate Video Retrieval Based on Spatiotemporal Pattern Tree;Fingerprint Liveness Detection Using Wavelet-Based Completed LBP Descriptor;silhouette-Based Real-Time Object Detection and Tracking;visual Object Detection for an Autonomous Indoor Robotic System;Engineering the Perception of Recognition Through Interactive Raw Primal Sketch by HNFGS and CNN-MRF;an Efficient Algorithm for Medical image Fusion Using Nonsubsampled Shearlet Transform;effective Denoising with Non-local Means Filter for Reliable Unwrapping of digital Holographic Interferometric Fringes;a Novel Text Localization Scheme for Camera Captured Document images;video Inpainting Based on Re-weighted Tensor Decomposition;deep Convolutional Neural Network for Person Re-identification: A Comprehensive Review;flexible Threshold Visual Odometry Algorithm Using Fuzzy Logics;fast Single image Learning-Based Super Resolution of Medical images Using a New Analytical Solution for Reconstruction Problem;analyzing ConvNets Depth for Deep Face Recognition;use of High-Speed Photography to Track and Analyze Melt Pool Quality in Selective Laser Sintering;multi-Scale Directional Mask Pattern for Medical image Classification and Retrieval;enhanced Characterness for Text Detection in the Wild;Denoising of Volumetric MR image Using Low-Rank Approximation on Tensor SVD Framework;iris Recognition Through Score-Level Fusion;V-LESS: A Video from Linear Event Summaries;action Recognition from Optical Flow Visualizations.

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2nd international conference on computer Vision and image processing, CVIP 2017

2nd International Conference on Computer Vision and Image Pr...

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2nd international conference on computer Vision and image processing, CVIP 2017

ISBN: (纸本)9789811078972

The proceedings contain 64 papers. The special focus in this conference is on. The topics include: A novel robust reversible watermarking technique based on prediction error expansion for medical images;integrated Feature Exploration for Handwritten Devanagari Numeral Recognition;Privacy Preserving for Annular Distribution Density Structure Descriptor in CBIR Using Bit-plane Randomization Encryption;near-Duplicate Video Retrieval Based on Spatiotemporal Pattern Tree;Fingerprint Liveness Detection Using Wavelet-Based Completed LBP Descriptor;silhouette-Based Real-Time Object Detection and Tracking;visual Object Detection for an Autonomous Indoor Robotic System;Engineering the Perception of Recognition Through Interactive Raw Primal Sketch by HNFGS and CNN-MRF;an Efficient Algorithm for Medical image Fusion Using Nonsubsampled Shearlet Transform;effective Denoising with Non-local Means Filter for Reliable Unwrapping of digital Holographic Interferometric Fringes;a Novel Text Localization Scheme for Camera Captured Document images;video Inpainting Based on Re-weighted Tensor Decomposition;deep Convolutional Neural Network for Person Re-identification: A Comprehensive Review;flexible Threshold Visual Odometry Algorithm Using Fuzzy Logics;fast Single image Learning-Based Super Resolution of Medical images Using a New Analytical Solution for Reconstruction Problem;analyzing ConvNets Depth for Deep Face Recognition;use of High-Speed Photography to Track and Analyze Melt Pool Quality in Selective Laser Sintering;multi-Scale Directional Mask Pattern for Medical image Classification and Retrieval;enhanced Characterness for Text Detection in the Wild;Denoising of Volumetric MR image Using Low-Rank Approximation on Tensor SVD Framework;iris Recognition Through Score-Level Fusion;V-LESS: A Video from Linear Event Summaries;action Recognition from Optical Flow Visualizations.

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Improving the quality of sound recovered using the visual microphone with frame-wise image denoising preprocessing 4

Improving the quality of sound recovered using the visual mi...

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4th international conference on computer graphics and digital image processing, cgdip 2020

作者： Choong, Ren-Jun Yap, Wun-She Chai Hum, Yan Kai Tee, Yee Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Selangor Kajang43000 Malaysia

The visual microphone is a passive remote sound recovery technique by analysing subtle vibrations in a video of an object vibrating due to sound. Multiple research endeavours have been done in improving the quality of the recovered sound, but so far none has been done on investigating the effect of denoising the videos frame by frame prior to the sound recovery using the visual microphone. This work fills in that gap, and evaluates the quality of the recovered sound based on human intelligibility metrics and simple signal-to-noise ratio metrics. Our best results indicated performing image denoising before sound recovery can reduce the noise power by up to 47.16 %, increase the intelligibility by 9.11 % and signal-to-noise ratio by 17.97 %. It is important to perform image denoising before sound recovery when the recorded videos are very noisy. © Published under licence by IOP Publishing Ltd.

关键词： image denoising

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A Multi-Level Thresholding image Segmentation Based on an Improved Artificial Bee Colony Algorithm 2nd

A Multi-Level Thresholding Image Segmentation Based on an Im...

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2nd EAI international conference on Robotic Sensor Networks, ROSENET 2018

作者： Xia, Xingyu Gao, Hao Hu, Haidong Lan, Rushi Pun, Chi-Man The Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China Department of Computer and Information Science University of Macau China Beijing Institute of Control Engineering Beijing China Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9783030177621

As a popular evolutionary algorithm, artificial bee colony (ABC) algorithm has been successfully applied into the threshold-based image segmentation problem. Based on our analysis, we find that the Otsu segmentation function is separable which means each variable is independent. Due to its one-dimensional search strategy and relative power global but poorer local search abilities, ABC could find an acceptable but not precise segmentation results. For making more precise search and further enhancing the achievements on image segmentation, we propose an Otsu segmentation method based on a new ABC algorithm with an improved scout bee strategy. Different from the traditional scout bee strategy, we use a local search strategy when a bee stagnates for a defined value. The experimental results on Berkeley segmentation database demonstrate the effectiveness of our algorithm. © 2020, Springer Science and Business Media Deutschland GmbH. All rights reserved.

关键词： image segmentation

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Evidence Building for Ad Click or Web Access on Cloud 2nd

Evidence Building for Ad Click or Web Access on Cloud

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2nd international conference on Machine Learning, image processing, Network Security and Data Sciences, MInd 2020

作者： Keserwani, Pankaj Kumar Govil, Mahesh Chandra Shubhakar, Pilli Emmanuel Department of Computer Science and Engineering National Institute of Technology Sikkim Burfang Block Ravangla South Sikkim737139 India Department of Computer Science and Engineering Malaviya National Institute of Technology Jaipur JLN Marg JaipurRajasthan India

ISBN: (纸本)9789811563171

Web related illegal activities are increasing beyond expectation in recent years. Association of National Advertisers has reported that businesses lost more than $6.5 billion in 2017 due to fraudulent activities of ad frauds. Website of Github was down on 28 February, 2018 due to Distributed Denial of Services (DDoS) attack. The attack of DDoS was conducted through memcached servers. Analysis on relevant log data (web access log or ad click log) is required to identify such illegal incidents in digital forensics investigation. An evidence building methodology is proposed and implemented to generate required log data. The proof of concept is provided by coding three scripts, two in python and one in JavaScript. Virtual Machine (VM) on Amazon Web Service (AWS) has been utilized to execute one python script for log separation. Second python script is executed on client database server to store fingerprint of each click or web access. Fingerprint is a generated hash value unique for each device accessing a website or clicking an advertisement (ad). The third JavaScript code is to be embedded in client web page(s) or ad. The verification of log data has also been discussed with the help of fingerprints. The verification process allows regenerating the fingerprints of log data stored in AWS data store. The regenerated fingerprints are being matched with fingerprints stored in client’s database server. The proposed methodology can identify malicious intention of the cloud service provider (CSP) or the investigator or attacker. The proposed methodology can be extended to cloud forensics. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Python

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2nd international Workshop on Reproducible Research in Pattern Recognition, RRPR 2018

2nd International Workshop on Reproducible Research in Patte...

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2nd international Workshop on Reproducible Research in Pattern Recognition, RRPR 2018

ISBN: (纸本)9783030239862

The proceedings contain 14 papers. The special focus in this conference is on Reproducible Research in Pattern Recognition. The topics include: Some Comments on Variational Bayes Block Sparse Modeling with Correlated Entries;an image processing Library in Modern C++: Getting Simplicity and Efficiency with Generic Programming;new Definition of Quality-Scale Robustness for image processing Algorithms, with Generalized Uncertainty Modeling, Applied to Denoising and Segmentation;reScience C: A Journal for Reproducible Replications in Computational Science;an Overview of Platforms for Reproducible Research and Augmented Publications;a Root-to-Leaf Algorithm Computing the Tree of Shapes of an image;discrete Regular Polygons for digital Shape Rigid Motion via Polygonization;non-deterministic Behavior of Ranking-Based Metrics When Evaluating Embeddings;CNN Implementation for Semantic Heads Segmentation Using Top-View Depth Data in Crowded Environment;Connected Components Labeling on DRAGs: Implementation and Reproducibility Notes;MATLAB Implementation Details of a Scalable Spectral Clustering Algorithm with the Cosine Similarity;On the Implementation of ALFA – Agglomerative Late Fusion Algorithm for Object Detection.

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A Pattern Analysis-based Segmentation to Localize Early and Late Blight Disease Lesions in digital images of Plant Leaves

A Pattern Analysis-based Segmentation to Localize Early and ...

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IEEE international conference on Signal and image processing Applications (IEEE ICSIPA)

作者： Abdu, Aliyu Muhammad Mokji, Musa Mohd Sheikh, Usman Ullah Univ Technol Malaysia Sch Elect Engn Skudai 81310 Malaysia

ISBN: (纸本)9781728133775

This study reports a disease symptom classification algorithm using a proposed pattern recognition approach to individually localize early and late blight visual disease symptoms. The algorithm uses the pathological analogy hierarchy of the diseases to produce a novel homogeneous pattern localization, more informative to extract features that would be utilized for a machine learning system to classify the two diseases in digital photographs of vegetable plants. One of the most significant advantages of the proposed pattern analysis is localizing symptomatic and necrotic regions based on pathological disease analogy using soft computing, with which the pattern of each disease manifestation along the leaf surface can be tracked and quantified for characterization. In the 1st phase of the experiment, individual symptomatic (R-S), necrotic (R-N), and blurred (R-B, in-between healthy and symptomatic) regions were identified, segmented, and quantified. The 2nd phase focuses on the extraction of pattern features for classification and severity estimation with a machine learning classifier. The obtained results are encouraging, successfully localizing and quantifying individual disease lesions. This also indicates the enhanced applicability of the proposed approach discriminating the two diseases based on their dissimilarity. It is also envisaged that the algorithm can be extended to other plant disease symptoms. Moreover, it provides opportunities for early identification and detection of subtle changes in plant growth, disease stage, and severity estimation to assisting crop diagnostics in precision agriculture.

关键词： Pattern analysis computer vision Segmentation Plant disease lesion Plant disease detection

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Nail image Segmentation for Disease Detection 2nd

Nail Image Segmentation for Disease Detection

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2nd international conference on Recent Trends in image processing and Pattern Recognition, RTIP2R 2018

作者： Marulkar, Shweta Mente, Rajivkumar Yashvantrao Chavan Institute of Science Satara India School of Computational Sciences Solapur University Solapur India

ISBN: (纸本)9789811391835

During modern era digital image processing in medical field is very popular concept. Number of diseases such as cancer, kidney disease, heart disease, brain haemorrhage etc. can be detected by capturing various types of images like MRI, CT Scan, PET, X-ray. Color feature of fingernail is used for disease detection. Various segmentation techniques like k-means segmentation, L*a*b color space, watershade segmentation are used to extract interested region. The segmented area used for the feature extraction and the disease can be detected. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Diseases

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