Int. J. Image Graph.最新文献_第6页

A Review on Natural Disaster Detection in Social Media and Satellite Imagery Using Machine Learning and Deep Learning 基于机器学习和深度学习的社交媒体和卫星图像自然灾害检测综述

Int. J. Image Graph. Pub Date : 2021-10-06 DOI: 10.1142/s0219467822500401

Swapandeep Kaur, Sheifali Gupta, Swati Singh, Tanvi Arora

引用次数: 2

Enhanced Face Recognition Using Adaptive Local Tri Weber Pattern with Improved Deep Learning Architecture 基于改进深度学习架构的自适应局部Tri Weber模式增强人脸识别

Int. J. Image Graph. Pub Date : 2021-10-06 DOI: 10.1142/s0219467822500528

R. Jatain, Manisha Jailia

{"title":"Enhanced Face Recognition Using Adaptive Local Tri Weber Pattern with Improved Deep Learning Architecture","authors":"R. Jatain, Manisha Jailia","doi":"10.1142/s0219467822500528","DOIUrl":"https://doi.org/10.1142/s0219467822500528","url":null,"abstract":"Effective face recognition is accomplished using the extraction of features and classification. Though there are multiple techniques for face image recognition, full face recognition in real-time is quite difficult. One of the emerging and promising methods to address this challenge in face recognition is deep learning networks. The inevitable network tool associated with the face recognition method with deep learning systems is convolutional neural networks (CNNs). This research intends to develop a new method for face recognition using adaptive intelligent methods. The main phases of the proposed method are (a) data collection, (b) image pre-processing, (c) normalization, (d) pattern extraction, and (e) recognition. Initially, the images for face recognition are gathered from CPFW, Yale datasets, and the MIT-CBCL dataset. The image pre-processing is performed by the Gaussian filtering method. Further, the normalization of the image will be done, which is a process that alters the range of pixel intensities and can handle the poor contrast due to glare. Then a new descriptor called adaptive local tri Weber pattern (ALTrWP) acts as a pattern extractor. In the recognition phase, the VGG16 architecture with new chick updated-chicken swarm optimization (NSU-CSO) is used. As the modification, VGG16 architecture will be enhanced by this optimization technique. The performance of the developed method is analyzed on two standards face database. Experimental results are compared with different machine learning approaches concerned with noteworthy measures, which demonstrate the efficiency of the considered classifier.","PeriodicalId":177479,"journal":{"name":"Int. J. Image Graph.","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123628745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Performance Analysis of Two-Stage Iterative Ensemble Method over Random Oversampling Methods on Multiclass Imbalanced Datasets 多类不平衡数据集上两阶段迭代集成方法优于随机过采样方法的性能分析

Int. J. Image Graph. Pub Date : 2021-10-06 DOI: 10.1142/s0219467822500255

S. Sridhar, K. Anbarasan

{"title":"Performance Analysis of Two-Stage Iterative Ensemble Method over Random Oversampling Methods on Multiclass Imbalanced Datasets","authors":"S. Sridhar, K. Anbarasan","doi":"10.1142/s0219467822500255","DOIUrl":"https://doi.org/10.1142/s0219467822500255","url":null,"abstract":"Data imbalance occurring among multiclass datasets is very common in real-world applications. Existing studies reveal that various attempts were made in the past to overcome this multiclass imbalance problem, which is a severe issue related to the typical supervised machine learning methods such as classification and regression. But, still there exists a need to handle the imbalance problem efficiently as the datasets include both safe and unsafe minority samples. Most of the widely used oversampling techniques like SMOTE and its variants face challenges in replicating or generating the new data instances for balancing them across multiple classes, particularly when the imbalance is high and the number of rare samples count is too minimal thus leading the classifier to misclassify the data instances. To lessen this problem, we proposed a new data balancing method namely a two-stage iterative ensemble method to tackle the imbalance in multiclass environment. The proposed approach focuses on the rare minority sample’s influence on learning from imbalanced datasets and the main idea of the proposed approach is to balance the data without any change in class distribution before it gets trained by the learner such that it improves the learner’s learning process. Also, the proposed approach is compared against two widely used oversampling techniques and the results reveals that the proposed approach shows a much significant improvement in the learning process among the multiclass imbalanced data.","PeriodicalId":177479,"journal":{"name":"Int. J. Image Graph.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122548635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Data Ownership and Secure Medical Data Transmission using Optimal Multiple Key-Based Homomorphic Encryption with Hyperledger Blockchain 基于Hyperledger区块链的最优多密钥同态加密的数据所有权和安全医疗数据传输

Int. J. Image Graph. Pub Date : 2021-10-06 DOI: 10.1142/s0219467822400034

Naresh Sammeta, L. Parthiban

{"title":"Data Ownership and Secure Medical Data Transmission using Optimal Multiple Key-Based Homomorphic Encryption with Hyperledger Blockchain","authors":"Naresh Sammeta, L. Parthiban","doi":"10.1142/s0219467822400034","DOIUrl":"https://doi.org/10.1142/s0219467822400034","url":null,"abstract":"Recent healthcare systems are defined as highly complex and expensive. But it can be decreased with enhanced electronic health records (EHR) management, using blockchain technology. The healthcare sector in today’s world needs to address two major issues, namely data ownership and data security. Therefore, blockchain technology is employed to access and distribute the EHRs. With this motivation, this paper presents novel data ownership and secure medical data transmission model using optimal multiple key-based homomorphic encryption (MHE) with Hyperledger blockchain (OMHE-HBC). The presented OMHE-HBC model enables the patients to access their own data, provide permission to hospital authorities, revoke permission from hospital authorities, and permit emergency contacts. The proposed model involves the MHE technique to securely transmit the data to the cloud and prevent unauthorized access to it. Besides, the optimal key generation process in the MHE technique takes place using a hosted cuckoo optimization (HCO) algorithm. In addition, the proposed model enables sharing of EHRs by the use of multi-channel HBC, which makes use of one blockchain to save patient visits and another one for the medical institutions in recoding links that point to EHRs stored in external systems. A complete set of experiments were carried out in order to validate the performance of the suggested model, and the results were analyzed under many aspects. A comprehensive comparison of results analysis reveals that the suggested model outperforms the other techniques.","PeriodicalId":177479,"journal":{"name":"Int. J. Image Graph.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116551502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic Shadow Detection and Removal for Vehicle Tracking System 车辆跟踪系统的动态阴影检测与去除

Int. J. Image Graph. Pub Date : 2021-10-06 DOI: 10.1142/s0219467822500504

Kalpesh R. Jadav, Arvind R. Yadav

引用次数: 0

Human Action Recognition Using Spatio-Temporal Multiplier Network and Attentive Correlated Temporal Feature 基于时空乘数网络和注意相关时间特征的人体动作识别

Int. J. Image Graph. Pub Date : 2021-10-06 DOI: 10.1142/s0219467822500516

C. Indhumathi, V. Murugan, G. Muthulakshmii

引用次数: 4

Image De-Speckling Based on the Coefficient of Variation, Improved Guided Filter, and Fast Bilateral Filter 基于变异系数、改进制导滤波器和快速双边滤波器的图像去斑

Int. J. Image Graph. Pub Date : 2021-09-25 DOI: 10.1142/s021946782250036x

Hadi Salehi

引用次数: 1

Enhancement of Vascular Patterns in Palm Images Using Various Image Enhancement Techniques for Person Identification 利用各种图像增强技术增强手掌图像中的血管模式，用于人物识别

Int. J. Image Graph. Pub Date : 2021-08-11 DOI: 10.1142/s0219467822500322

M. Rajalakshmi, K. Annapurani

{"title":"Enhancement of Vascular Patterns in Palm Images Using Various Image Enhancement Techniques for Person Identification","authors":"M. Rajalakshmi, K. Annapurani","doi":"10.1142/s0219467822500322","DOIUrl":"https://doi.org/10.1142/s0219467822500322","url":null,"abstract":"Image classification is a complicated process of classifying an image based on its visual representation. This paper portrays the need for adapting and applying a suitable image enhancement and denoising technique in order to arrive at a successful classification of data captured remotely. Biometric properties that are widely explored today are very important for authentication purposes. Noise may be the result of incorrect vein detection in the accepted image, thus explaining the need for a better development technique. This work provides subjective and objective analysis of the performance of various image enhancement filters in the spatial domain. After performing these pre-processing steps, the vein map and the corresponding vein graph can be easily obtained with minimal extraction steps, in which the appropriate Graph Matching method can be used to evaluate hand vein graphs thus performing the person authentication. The analysis result shows that the image enhancement filter performs better as an image enhancement filter compared to all other filters. Image quality measures (IQMs) are also tabulated for the evaluation of image quality.","PeriodicalId":177479,"journal":{"name":"Int. J. Image Graph.","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134625339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Detection and Correction of Multi-Warping Document Image 多重扭曲文档图像的检测与校正

Int. J. Image Graph. Pub Date : 2021-07-30 DOI: 10.1142/s0219467822500346

M. Wagdy, Khaild Amin, Mina Ibrahim

引用次数: 1

New Set of Invariant Quaternion Krawtchouk Moments for Color Image Representation and Recognition 用于彩色图像表示和识别的一种新的不变四元数克劳恰克矩集

Int. J. Image Graph. Pub Date : 2021-07-23 DOI: 10.1142/S0219467822500371

Gaber Hassan, K. Hosny, R. M. Farouk, A. Alzohairy

引用次数: 4