Search results

1 – 10 of 435
Article
Publication date: 16 July 2021

Shiya Li, Usman Waheed, Mohanad Bahshwan, Louis Zizhao Wang, Livia Mariadaria Kalossaka, Jiwoo Choi, Franciska Kundrak, Alexandros Lattas, Stylianos Ploumpis, Stefanos Zafeiriou and Connor William Myant

A three-dimensional (3D) printed custom-fit respirator mask has been proposed as a promising solution to alleviate mask-related injuries and supply shortages during…

Abstract

Purpose

A three-dimensional (3D) printed custom-fit respirator mask has been proposed as a promising solution to alleviate mask-related injuries and supply shortages during COVID-19. However, creating a custom-fit computer-aided design (CAD) model for each mask is currently a manual process and thereby not scalable for a pandemic crisis. This paper aims to develop a novel design process to reduce overall design cost and time, thus enabling the mass customisation of 3D printed respirator masks.

Design/methodology/approach

Four data acquisition methods were used to collect 3D facial data from five volunteers. Geometric accuracy, equipment cost and acquisition time of each method were evaluated to identify the most suitable acquisition method for a pandemic crisis. Subsequently, a novel three-step design process was developed and scripted to generate respirator mask CAD models for each volunteer. Computational time was evaluated and geometric accuracy of the masks was evaluated via one-sided Hausdorff distance.

Findings

Respirator masks were successfully generated from all meshes, taking <2 min/mask for meshes of 50,000∼100,000 vertices and <4 min for meshes of ∼500,000 vertices. The average geometric accuracy of the mask ranged from 0.3 mm to 1.35 mm, depending on the acquisition method. The average geometric accuracy of mesh obtained from different acquisition methods ranged from 0.56 mm to 1.35 mm. A smartphone with a depth sensor was found to be the most appropriate acquisition method.

Originality/value

A novel and scalable mass customisation design process was presented, which can automatically generate CAD models of custom-fit respirator masks in a few minutes from a raw 3D facial mesh. Four acquisition methods, including the use of a statistical shape model, a smartphone with a depth sensor, a light stage and a structured light scanner were compared; one method was recommended for use in a pandemic crisis considering equipment cost, acquisition time and geometric accuracy.

Details

Rapid Prototyping Journal, vol. 27 no. 7
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 31 July 2020

Zainab Akhtar, Jong Weon Lee, Muhammad Attique Khan, Muhammad Sharif, Sajid Ali Khan and Naveed Riaz

In artificial intelligence, the optical character recognition (OCR) is an active research area based on famous applications such as automation and transformation of…

Abstract

Purpose

In artificial intelligence, the optical character recognition (OCR) is an active research area based on famous applications such as automation and transformation of printed documents into machine-readable text document. The major purpose of OCR in academia and banks is to achieve a significant performance to save storage space.

Design/methodology/approach

A novel technique is proposed for automated OCR based on multi-properties features fusion and selection. The features are fused using serially formulation and output passed to partial least square (PLS) based selection method. The selection is done based on the entropy fitness function. The final features are classified by an ensemble classifier.

Findings

The presented method was extensively tested on two datasets such as the authors proposed and Chars74k benchmark and achieved an accuracy of 91.2 and 99.9%. Comparing the results with existing techniques, it is found that the proposed method gives improved performance.

Originality/value

The technique presented in this work will help for license plate recognition and text conversion from a printed document to machine-readable.

Details

Journal of Enterprise Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 26 August 2014

Xing Wang, Zhenfeng Shao, Xiran Zhou and Jun Liu

This paper aims to present a novel feature design that is able to precisely describe salient objects in images. With the development of space survey, sensor and…

Abstract

Purpose

This paper aims to present a novel feature design that is able to precisely describe salient objects in images. With the development of space survey, sensor and information acquisition technologies, more complex objects appear in high-resolution remote sensing images. Traditional visual features are no longer precise enough to describe the images.

Design/methodology/approach

A novel remote sensing image retrieval method based on VSP (visual salient point) features is proposed in this paper. A key point detector and descriptor are used to extract the critical features and their descriptors in remote sensing images. A visual attention model is adopted to calculate the saliency map of the images, separating the salient regions from the background in the images. The key points in the salient regions are then extracted and defined as VSPs. The VSP features can then be constructed. The similarity between images is measured using the VSP features.

Findings

According to the experiment results, compared with traditional visual features, VSP features are more precise and stable in representing diverse remote sensing images. The proposed method performs better than the traditional methods in image retrieval precision.

Originality/value

This paper presents a novel remote sensing image retrieval method based on VSP features.

Details

Sensor Review, vol. 34 no. 4
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 11 June 2018

Deepika Kishor Nagthane and Archana M. Rajurkar

One of the main reasons for increase in mortality rate in woman is breast cancer. Accurate early detection of breast cancer seems to be the only solution for diagnosis. In…

Abstract

Purpose

One of the main reasons for increase in mortality rate in woman is breast cancer. Accurate early detection of breast cancer seems to be the only solution for diagnosis. In the field of breast cancer research, many new computer-aided diagnosis systems have been developed to reduce the diagnostic test false positives because of the subtle appearance of breast cancer tissues. The purpose of this study is to develop the diagnosis technique for breast cancer using LCFS and TreeHiCARe classifier model.

Design/methodology/approach

The proposed diagnosis methodology initiates with the pre-processing procedure. Subsequently, feature extraction is performed. In feature extraction, the image features which preserve the characteristics of the breast tissues are extracted. Consequently, feature selection is performed by the proposed least-mean-square (LMS)-Cuckoo search feature selection (LCFS) algorithm. The feature selection from the vast range of the features extracted from the images is performed with the help of the optimal cut point provided by the LCS algorithm. Then, the image transaction database table is developed using the keywords of the training images and feature vectors. The transaction resembles the itemset and the association rules are generated from the transaction representation based on a priori algorithm with high conviction ratio and lift. After association rule generation, the proposed TreeHiCARe classifier model emanates in the diagnosis methodology. In TreeHICARe classifier, a new feature index is developed for the selection of a central feature for the decision tree centered on which the classification of images into normal or abnormal is performed.

Findings

The performance of the proposed method is validated over existing works using accuracy, sensitivity and specificity measures. The experimentation of proposed method on Mammographic Image Analysis Society database resulted in classification of normal and abnormal cancerous mammogram images with an accuracy of 0.8289, sensitivity of 0.9333 and specificity of 0.7273.

Originality/value

This paper proposes a new approach for the breast cancer diagnosis system by using mammogram images. The proposed method uses two new algorithms: LCFS and TreeHiCARe. LCFS is used to select optimal feature split points, and TreeHiCARe is the decision tree classifier model based on association rule agreements.

Details

Sensor Review, vol. 39 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 26 May 2020

S. Veluchamy and L.R. Karlmarx

Biometric identification system has become emerging research field because of its wide applications in the fields of security. This study (multimodal system) aims to find…

Abstract

Purpose

Biometric identification system has become emerging research field because of its wide applications in the fields of security. This study (multimodal system) aims to find more applications than the unimodal system because of their high user acceptance value, better recognition accuracy and low-cost sensors. The biometric identification using the finger knuckle and the palmprint finds more application than other features because of its unique features.

Design/methodology/approach

The proposed model performs the user authentication through the extracted features from both the palmprint and the finger knuckle images. The two major processes in the proposed system are feature extraction and classification. The proposed model extracts the features from the palmprint and the finger knuckle with the proposed HE-Co-HOG model after the pre-processing. The proposed HE-Co-HOG model finds the Palmprint HE-Co-HOG vector and the finger knuckle HE-Co-HOG vector. These features from both the palmprint and the finger knuckle are combined with the optimal weight score from the fractional firefly (FFF) algorithm. The layered k-SVM classifier classifies each person's identity from the fused vector.

Findings

Two standard data sets with the palmprint and the finger knuckle images were used for the simulation. The simulation results were analyzed in two ways. In the first method, the bin sizes of the HE-Co-HOG vector were varied for the various training of the data set. In the second method, the performance of the proposed model was compared with the existing models for the different training size of the data set. From the simulation results, the proposed model has achieved a maximum accuracy of 0.95 and the lowest false acceptance rate and false rejection rate with a value of 0.1.

Originality/value

In this paper, the multimodal biometric recognition system based on the proposed HE-Co-HOG with the k-SVM and the FFF is developed. The proposed model uses the palmprint and the finger knuckle images as the biometrics. The development of the proposed HE-Co-HOG vector is done by modifying the Co-HOG with the holoentropy weights.

Details

Sensor Review, vol. 40 no. 2
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 15 June 2020

Yang Zhang, Wei Liu, Yongkang Lu, Xikang Cheng, Weiqi Luo, Hongtu Di and Fuji Wang

Profile measurement with boundary information plays a vital role in the detection of quality in the assembly of aviation parts. The purpose of this paper is to improve the…

Abstract

Purpose

Profile measurement with boundary information plays a vital role in the detection of quality in the assembly of aviation parts. The purpose of this paper is to improve the evaluation accuracy of the aerodynamic shapes of airplanes, the profiles of large-sized parts need to be measured accurately.

Design/methodology/approach

In this paper, an accurate profile measurement method based on boundary reference points is proposed for the industrial stereo-vision system. Based on the boundary-reference points, the authors established a priori constraint for extracting the boundary of the measured part. Combining with the image features of background and the measured part, an image-edge compensation model is established to extract the boundary of the measured part. The critical point of a laser stripe on the edge of the measured part is extracted corresponding to the boundary constraint. Finally, as per the principle of binocular vision, the profile of the measured part is reconstructed.

Finding

Laboratory experiments validate the measurement accuracy of the proposed method which is 0.33 mm. In the analysis of results between the measured data and the theoretical model, the measuring accuracy of the proposed method was found to be significantly higher than that of the other traditional methods.

Practical implication

An aviation part was measured in the part-assembly shop by the proposed method, which verified the feasibility and effectiveness of this method. The research can realize the measurement of smooth surface boundary which can solve existing profile reconstruction problems for aviation parts.

Originality/value

According to the two-dimensional contour constraint, critical points of the laser strip sequence at the edge of measured part are extracted and the accurate profile reconstruction with the boundary is realized.

Details

Sensor Review, vol. 40 no. 4
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 27 August 2019

Min Hao, Guangyuan Liu, Desheng Xie, Ming Ye and Jing Cai

Happiness is an important mental emotion and yet becoming a major health concern nowadays. For this reason, better recognizing the objective understanding of how humans…

Abstract

Purpose

Happiness is an important mental emotion and yet becoming a major health concern nowadays. For this reason, better recognizing the objective understanding of how humans respond to event-related observations in their daily lives is especially important.

Design/methodology/approach

This paper uses non-intrusive technology (hyperspectral imaging [HSI]) for happiness recognition. Experimental setup is conducted for data collection in real-life environments where observers are showing spontaneous expressions of emotions (calm, happy, unhappy: angry) during the experimental process. Based on facial imaging captured from HSI, this work collects our emotional database defined as SWU Happiness DB and studies whether the physiological signal (i.e. tissue oxygen saturation [StO2], obtained by an optical absorption model) can be used to recognize observer happiness automatically. It proposes a novel method to capture local dynamic patterns (LDP) in facial regions, introducing local variations in facial StO2 to fully use physiological characteristics with regard to hyperspectral patterns. Further, it applies a linear discriminant analysis-based support vector machine to recognize happiness patterns.

Findings

The results show that the best classification accuracy is 97.89 per cent, objectively demonstrating a feasible application of LDP features on happiness recognition.

Originality/value

This paper proposes a novel feature (i.e. LDP) to represent the local variations in facial StO2 for modeling the active happiness. It provides a possible extension to the promising practical application.

Details

Engineering Computations, vol. 37 no. 1
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 1 October 2000

D. Dutta Majumder and M. Bhattacharya

The cybernetic approach differs significantly from the conventional reductionist methods of natural and biological sciences. Norbert Wiener established the theory of…

Abstract

The cybernetic approach differs significantly from the conventional reductionist methods of natural and biological sciences. Norbert Wiener established the theory of cybernetics as a science of control and communication process in living beings (human and animals) and machines. Dutta Majumder in his Norbert Wiener Award winning paper extended the approach to include integrated complex human machine systems and functions with general systems theory as a unitary science laying the mathematical foundation for unifying observing systems, observed systems and the act of observing as indicated in von Foerster’s concept of second‐order cybernetics. Both from the point of view of ontology and that of epistemology the cybernetic approach now enables computer technology to incorporate artificial intelligence (AI) and expert system (ES) for knowledge based instrumentation for diagnostics and therapy planning. Presents the results of a project for development of a knowledge based framework for combining different modalities of medical image processing such as CT, MR(T1), MR(T2), SPECT, PET, USG etc. whichever is relevant for particular pathological investigation for diagnostics and therapeutic planning. Experiments were conducted with (a) Alzheimer’s patient data and (b) detection and grading of malignancy with oncological data for the cancer screening system.

Details

Kybernetes, vol. 29 no. 7/8
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 8 November 2019

Wei-Yen Hsu

Virtual medical instrumentation plays a vital role in a telemedicine system that obtains data from the medical instrument, required by doctors at remote location to…

Abstract

Purposed

Virtual medical instrumentation plays a vital role in a telemedicine system that obtains data from the medical instrument, required by doctors at remote location to diagnose a patient. In recent years, the analysis of skin quality by telemedicine system has become an emerging trend. To allow the skin to complement the beauty products and achieve better improvement results, the purpose of this study is to provide advice on a system that can objectively evaluate the condition of the skin of the face and to match appropriate beauty and cosmetic products.

Design/methodology/approach

A novel customer-oriented medical system is proposed for the applications of telemedicine in this study, whose aim is to improve information transfer quality and rate to further enhance the communication between medical staffs and patients in the telemedicine. More specifically, facial skin will be recorded with digital images, and skin detection will be performed using image processing technology to facilitate doctors to provide medical treatment for the patients at far end.

Findings

The roughness, freckles and acne indicators were evaluated after obtaining skin images. These three indicators were used as input to the system, and skin scores were then calculated to evaluate skin conditions to further provide more matching skin care.

Originality/value

This can improve the health problems that have occurred and can also record the skin condition for each test. Experimental results suggest that it is suitable for the applications of telemedicine.

Details

The Electronic Library, vol. 37 no. 6
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 22 March 2021

Naganagouda Patil, Preethi N. Patil and P.V. Rao

The abnormalities of glaucoma have high impact on deciding and representing the causes that effects severity of blindness in human beings. The simulation experimental…

Abstract

Purpose

The abnormalities of glaucoma have high impact on deciding and representing the causes that effects severity of blindness in human beings. The simulation experimental results would help the ophthalmologist in diagnosing of glaucoma abnormality accurately. The significant effect of glaucoma has a huge impact on the quality of human life, and its growth rate in world population tremendously increases. Glaucoma is considered as second largest cause for the blindness in the world; hence identification of it marks the importance of its detection at the earliest.

Design/methodology/approach

The prime objective of the work proposed is to build up a human intervention free image preparing framework for glaucoma screening. The disc calculation is assessed on retinal image dataset called retinal Image for glaucoma Analysis. The proposed method briefs a novel optic disc division calculation depending on applying a level-set strategy on a confined optic disc image. In the instance of low quality image, a twofold level set is designed, in which the principal level set is viewed as restriction for the optic disc. To keep the veins from meddling with the level-set procedure, an inpainting strategy has been applied. Also a significant commitment is to include the varieties in notion adopted by the ophthalmologists in distinguishing the disc localization and diagnosing the glaucoma. Most of the past investigations are prepared and tested depending on just a single feature, which can be thought to be one-sided for the ophthalmologist.

Findings

In continuation, the correctness has been determined depending on the quantity of image that matched with the investigation pattern adopted by the ophthalmologist. The 175 retinal images were utilized to test the results of proposed work with the manual markings of ophthalmologists. The error-free calculation in marking the optic disc region and centroid was 98.95% in comparison with the existing result of 87.34%.

Originality/value

In continuation, the correctness has been determined depending on the quantity of image that matched with the investigation pattern adopted by the ophthalmologist. The 175 retinal images were utilized to test the results of proposed work with the manual markings of ophthalmologists. The error-free calculation in marking the optic disc region and centroid was 98.95% in comparison with the existing result of 87.34%.

Details

International Journal of Intelligent Unmanned Systems, vol. 10 no. 1
Type: Research Article
ISSN: 2049-6427

Keywords

1 – 10 of 435