Augmented reality (AR) has proven to be an invaluable interactive medium to reduce cognitive load by bridging the gap between the task-at-hand and relevant information by displaying information wit...

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2020.1859636

Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review

A 3D model encryption scheme based on a cascaded chaotic system

Nowadays the market is becoming increasingly competitive, factories are required not only to enhance the product quality but also to reduce manufacturing and maintenance times. In an industrial context, modern factories are composed by many automated systems, such as industrial robots, which can perform different tasks. Although industrial robots are becoming more powerful and efficient, human workers are still required to accomplish different operations, such as training and maintenance procedures. The proposed research aims to assess a remote interaction system in an industrial training collaborative mixed-reality (CMR) environment. A remote expert user is capable of explaining a training procedure to an unskilled local user. Remote and local users interact using different interaction systems: the remote operator gives assistance using an immersive Virtual Reality (VR) device, whereas the local user interacts using a wearable Augmented Reality (AR) device. A comparison between an interaction based on the presence of a virtual human and one based on the use of abstract icons is proposed. In the first case, a virtual 3D representation of the remote technician is shown to the local user by using AR: the remote technician can pinpoint the components involved in the training procedure and the local user can visualize the instructions through some animations of the virtual avatar. In the second case, the local user cannot see a 3D representation of the remote technician; on the other hand, different 3D models, such as animated icons, are displayed to the local operator through AR depending on the component pinpointed by the remote technician in the virtual environment. Each 3D icon should suggest to the local user which component has to be manipulated at the current step of the procedure. Preliminary results suggest that the interface that requires less resources to be developed and managed should be preferred. Although in no audio condition the virtual avatar may improve the sense of presence of the remote technician, the use of abstract metaphors seems to be of primary importance to successfully complete an industrial task.

/pdf/a-comparison-between-two-different-approaches-for-a-1k2l2i74pe.pdf

A Comparison Between Two Different Approaches for a Collaborative Mixed-Virtual Environment in Industrial Maintenance.

Surface defect inspection plays a vital role in leather manufacturing. Current practice involves an expert to inspect each piece of leather individually and detect defects manually. However, such a manual inspection is highly subjective and varies quite considerably from one assorter to another. Computer vision system for natural material like leather is a challenging research problem. This study describes the application of computer vision system to capture leather surface images and use of a novel Fast Convergence Particle Swarm Optimization (FCPSO) algorithm on a set of handcrafted texture features viz., GLCM and classified using supervised classifiers viz., Multi Layer Perceptron (MLP), Decision Tree (DT), SVM, Naive Bayes, K-Nearest Neighbors (KNN) and Random Forest (RF). FCPSO using modified fitness function by selective band Shannon entropy is implemented to segment industrial leather images. Segmentation efficiency of the proposed FCPSO algorithm is evaluated and its performance is compared with other optimization algorithms. Efficiency of the segmentation algorithms is evaluated using performance measures such as average difference (AD), Area Error Rate (AER), Edge-based structural similarity index (ESSIM), F-Score, Normalized correlation coefficient (NK), Overlap Error (OE), structural content (SC), Structural similarity index (SSIM) and Zijdenbos similarity index (ZSI). Correlation of the segmented area using FCPSO with the experts’ ground truth is found to be high with R value of 0.84. Feature extraction is carried out using GLCM texture features and the most prominent features were selected using statistical t-test and correlation coefficient. Experimental results showed encouraging results for random forest classifier confirming the potential of the proposed system for automatic leather defect classification.

Vision based inspection system for leather surface defect detection using fast convergence particle swarm optimization ensemble classifier approach

Warning pedestrians of oncoming vehicles is very important for improving pedestrian safety. Due to the limitation of the pedestrian’s carrying ability, it is crucial to find an effective solution t...

https://journals.sagepub.com/doi/pdf/10.1177/1071181319631413

An Augmented-reality-based Warning Interface for Pedestrians: User Interface Design and Evaluation:

The Echocardiogram is an ultrasound test that uses high pitched sound waves through a transducer. This device picks up the echoes that bounce off from different parts of the brain. These echoes are converted to sequence of moving pictures with limited information. Echocardiogram videos are used to detect the valvular and muscle damage problems. These moving pictures have lots of vulnerability where prediction and decision making is a tedious process. An automated detection, diagnosis and classification of DCM and HCM disease using DPSO-FCM based segmentation is analyzed in this proposed work. The Echocardiogram videos or frame sequences are subjected to preprocessing using Gaussian filter. The preprocessed image is segmented by DPSO-FCM clustering, which effectively segments the Left Ventricle region. GLCM and DCT features are extracted from the segmented Normal, Dilated Cardiomyopathy (DCM) and Hypertrophic Cardiomyopathy (HCM) regions. The extracted features are analyzed and are classified for normal and abnormality using BPNN, Naive Bayes, SVM and Random Forest classifier. Simulation results clearly show better results which obtained 95% of segmentation accuracy and 90% of classification accuracy for the SVM classifier.

DPSO-FCM based segmentation and Classification of DCM and HCM Heart Diseases

Augmented Reality is a way newer technology to bring in field for the development of new applications so that it can be able to enhance the digital market in the upcoming years. This research paper is to have a knowledge of about how to implement this technology to bring the revolution all over the world, its benefits in using various fields and how augmented reality application would be easier in accessing the complicated virtual things in just one click.

Augmented Reality Application: AR Learning Platform for Primary Education

Tokenizing assets through the use of blockchain is the next big thing in digital currency markets. Securing the assets in the world of the internet is challenging as most of them can easily be copied and sold in the secondary market. Protecting the rights of the asset owner is one of the challenging research areas. NFTs (non-fungible tokens) are very useful in representing the ownership of unique items for any assets. NFTs ensure that an asset can have only one official owner at any point in time with the help of Ethereum-based blockchain network. Ethereum NFTs can ensure that no one can modify the ownership rights or copy and paste the digital assets. NFTs are a boon to the artists, musicians, and others who want to create impressive digital assets. The objective of this chapter is to take you to the world of NFTs and to explain how the NFTs are going to impact digital transactions in a bigger way in the future. This chapter covers the introduction, technical aspects, security impacts, use cases, and successful implementations of NFTs in various realms.

The World of NFTs (Non-Fungible Tokens): The Future of Blockchain and Asset Ownership

In the emerging Virtual Reality era, 3D multimedia contents are popularized as images and videos. Encryption is a methodology that enhances the security by converting the original content into unintelligible content. The Arnold transform or Arnold cat map is a commonly used chaos-based encryption system that encrypts by shuffling the data. 3D models include vertices, faces and textures. An efficient secure symmetric chaotic cryptosystem is proposed for 3D mesh graphical models using 3D Arnold cat map. Arnold cat map is performed to encrypt the 3D mesh model using shuffling and substitution. The cryptosystem is proposed for vertices and faces separately and are composited together to form the final encrypted model. Each round introduces a good permutation and substitution through the confusion and diffusion generated by the 3D Arnold map. The chaotic function delivers more security for the 3D models through the shuffling and substitution. Simulation results show that the proposed scheme encrypts and decrypts the 3D mesh models and resists various attacks.

A New Transformation of 3D Models Using Chaotic Encryption Based on Arnold Cat Map

The detection of cancer from the histology images with hematoxylin and eosin stained is significant, requires more analysis, and often leads to disagreement among pathologists. Computerized diagnostic systems help pathologists to enhance diagnostic accuracy and efficiency. Recent advances in this field have led them to successfully process histology images using convolution neural networks (CNNs). The classification from histology images into malignant and benign depends upon the cell density, variability, and tissue structure. The state and art of review of various research works using histology images are detailed in this work. The VGG16 model is also used to classify the breast cancer histology images into benign and malignant which achieved 88% accuracy on the testing data. The findings are likewise compared to other approaches.

Benson Edwin Raj

Papers

DPSO-FCM based segmentation and Classification of DCM and HCM Heart Diseases

Augmented Reality Application: AR Learning Platform for Primary Education

The World of NFTs (Non-Fungible Tokens): The Future of Blockchain and Asset Ownership

A New Transformation of 3D Models Using Chaotic Encryption Based on Arnold Cat Map

Breast cancer Analysis and Detection in Histopathological Images using CNN Approach