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Article
Publication date: 9 September 2013

Fevzi Karsli and Mustafa Dihkan

The purpose of this paper is to provide crystal size distribution (CSD) using photogrammetric and image analysis techniques. A new algorithm is proposed to detect CSDs and a…

Abstract

Purpose

The purpose of this paper is to provide crystal size distribution (CSD) using photogrammetric and image analysis techniques. A new algorithm is proposed to detect CSDs and a comparison is carried out with conventional watershed segmentation algorithm.

Design/methodology/approach

Polished granite plates were prepared to designate the metrics of CSD measurements. There are many important metrics for measurements on CSD. Some of them are orientation, size, position, area, aspect ratio, convexity, circularity, perimeter, convex hull, bounding box, eccentricity, shape, max-min length of CSD's fitted and corrected ellipse, and population density in a per unit area. Prior to image processing stage, camera calibration was performed to remove the image distortion errors. Image processing techniques were applied to corrected images for detecting the CSD parameters.

Findings

The proposed algorithm showed the improved preservation of size and shape characteristics of the crystal material when compared to the watershed segmentation. According to the experimental results, proposed algorithm revealed promising results in identifying CSDs more easily and efficiently.

Originality/value

This paper describes CSD of granitic rocks by using automated grain boundary detection methods in polished plate images. Some metrics of CSDs were detected by employing a new procedure. A computer-based image analysis technique was developed to measure the CSDs on the granitic rock plates. A validation is done by superimposing digitally detected CSD metrics to original samples.

Details

Sensor Review, vol. 33 no. 4
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 11 June 2019

Amitava Choudhury, Snehanshu Pal, Ruchira Naskar and Amitava Basumallick

The purpose of this paper is to develop an automated phase segmentation model from complex microstructure. The mechanical and physical properties of metals and alloys are…

Abstract

Purpose

The purpose of this paper is to develop an automated phase segmentation model from complex microstructure. The mechanical and physical properties of metals and alloys are influenced by their microstructure, and therefore the investigation of microstructure is essential. Coexistence of random or sometimes patterned distribution of different microstructural features such as phase, grains and defects makes microstructure highly complex, and accordingly identification or recognition of individual phase, grains and defects within a microstructure is difficult.

Design/methodology/approach

In this perspective, computer vision and image processing techniques are effective to help in understanding and proper interpretation of microscopic image. Microstructure-based image processing mainly focuses on image segmentation, boundary detection and grain size approximation. In this paper, a new approach is presented for automated phase segmentation from 2D microstructure images. The benefit of the proposed work is to identify dominated phase from complex microstructure images. The proposed model is trained and tested with 373 different ultra-high carbon steel (UHCS) microscopic images.

Findings

In this paper, Sobel and Watershed transformation algorithms are used for identification of dominating phases, and deep learning model has been used for identification of phase class from microstructural images.

Originality/value

For the first time, the authors have implemented edge detection followed by watershed segmentation and deep learning (convolutional neural network) to identify phases of UHCS microstructure.

Details

Engineering Computations, vol. 36 no. 6
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 3 May 2016

Liya Wang, Yang Zhao, Yaoming Zhou and Jingbin Hao

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

Abstract

Purpose

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

Design/methodology/approach

This paper proposes a new method of watershed segmentation based on morphology. A dimensional increment matrix calculation method and an image segmentation method combined with a fuzzy clustering algorithm are provided. The visibility of the segmented image and the segmentation accuracy of a defective image are guaranteed.

Findings

Compared with the traditional one, the segmentation result obtained in this study is superior in aspects of noise control and defect segmentation. It completely proves that the segmentation method proposed in this study is better matches the requirements of FPC defect extraction and can more effectively provide the segmentation result. Compared with traditional human operators, this system ensures greater accuracy and more objective detection results.

Research limitations/implications

The extraction of FPC defect characteristics contains some obvious characteristics as well as many implied characteristics. These characteristics can be extracted through specific space conversion and arithmetical operation. Therefore, more images are required for analysis and foresight to establish a more widely used FPC defect detection sorting algorithm.

Originality/value

This paper proposes a new method of watershed segmentation based on morphology. It combines a traditional edge detection algorithm and mathematical morphology. The FPC surface defect detection system can meet the requirements of online detection through constant design and improvement. Therefore, human operators will be replaced by machine vision, which can preferably reduce the production costs and improve the efficiency of FPC production.

Details

Circuit World, vol. 42 no. 2
Type: Research Article
ISSN: 0305-6120

Keywords

Article
Publication date: 6 August 2019

Peng Peng and Jiugen Wang

It is a challenging task to analysis oxide wear particles when they are stuck together with other types of wear particles in complex ferrography images. Hence, this paper aims to…

Abstract

Purpose

It is a challenging task to analysis oxide wear particles when they are stuck together with other types of wear particles in complex ferrography images. Hence, this paper aims to propose a method of ferrography image segmentation to analysis oxide wear debris in complex ferrography images.

Design/methodology/approach

First, ferrography images are segmented with watershed transform. Then, two region merging rules are proposed to improve the initial segmentation results. Finally, the features of each particle are extracted to detect and assess the oxide wear particles.

Findings

The results show that the proposed method outperforms other methods of ferrography image segmentation, and the overlapping wear particles in complex ferrography images can be well separated. Moreover, the features of each separated wear particles can be easily extracted to analysis the oxide wear particles.

Practical implications

The proposed method provides a useful approach for the automatic detection and assessment of oxide wear particles in complex ferrography images.

Originality/value

The colours, edges and position information of wear debris are considered in the proposed method to improve the segmentation result. Moreover, the proposed method can not only detect oxide wear particles in ferrography images but also evaluate oxide wear severity in ferrography images.

Details

Industrial Lubrication and Tribology, vol. 71 no. 7
Type: Research Article
ISSN: 0036-8792

Keywords

Article
Publication date: 4 July 2016

Tomasz Chady, Ryszard Sikora, Mariusz Szwagiel, Bogdan Grzywacz, Leszek Misztal, Pawel Waszczuk, Michal Szydlowski and Barbara Szymanik

The purpose of this paper is to describe a multisource system for nondestructive inspection of welded elements exploited in aircraft industry developed in West Pomeranian…

Abstract

Purpose

The purpose of this paper is to describe a multisource system for nondestructive inspection of welded elements exploited in aircraft industry developed in West Pomeranian University of Technology, Szczecin in the frame of CASELOT project. The system task is to support the operator in flaws identification of welded aircraft elements using data obtained from X-ray inspection and 3D triangulation laser scanners.

Design/methodology/approach

For proper defects detection a set of special processing algorithms were developed. For easier system exploitation and integration of all components a user friendly interface in LabVIEW environment was designed.

Findings

It is possible to create the fully independent, intelligent system for welds’ flaws detection. This kind of technology might be crucial in further development of aircraft industry.

Originality/value

In this paper a number of innovative solutions (new algorithms, algorithms’ combinations) for defects’ detection in welds are presented. All of these solutions are the basis of presented complete system. One of the main original solution is a combination of the systems based on 3D triangulation laser scanner and X-ray testing.

Details

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 35 no. 4
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 28 July 2020

Alan Clardy

The purpose of this paper is to develop an ontological foundation for future studies, based in part on integrating some prior albeit incomplete work in this area.

Abstract

Purpose

The purpose of this paper is to develop an ontological foundation for future studies, based in part on integrating some prior albeit incomplete work in this area.

Design/methodology/approach

This manuscript is based on a literature review, as well as on conceptual and theoretical enhancements from this subject field.

Findings

As the future does not exist (it is always something yet to come), the ontological foundations for studying the future must be based on the current reality of the physical, biological and social-psychological worlds of experience and ideas. From this basis, 10 postulates are provided that are based on that current reality and are applied to studying the future. Thus, by characterizing the current reality and how it is understood by people, meaningful statements about the future are possible.

Practical implications

For each ontological postulate, one or more implications for the study of the future are provided as guidelines for practice.

Originality/value

This manuscript integrates and builds on prior offerings about ontological concerns into a comprehensive framework that legitimates and focuses the practices of studying the future.

Details

foresight, vol. 22 no. 5/6
Type: Research Article
ISSN: 1463-6689

Keywords

Article
Publication date: 1 April 2014

Yelda Turkan, Frédéric Bosché, Carl T. Haas and Ralph Haas

Previous research has shown that “Scan-vs-BIM” object recognition systems, which fuse three dimensional (3D) point clouds from terrestrial laser scanning (TLS) or digital…

Abstract

Purpose

Previous research has shown that “Scan-vs-BIM” object recognition systems, which fuse three dimensional (3D) point clouds from terrestrial laser scanning (TLS) or digital photogrammetry with 4D project building information models (BIM), provide valuable information for tracking construction works. However, until now, the potential of these systems has been demonstrated for tracking progress of permanent structural works only; no work has been reported yet on tracking secondary or temporary structures. For structural concrete work, temporary structures include formwork, scaffolding and shoring, while secondary components include rebar. Together, they constitute most of the earned value in concrete work. The impact of tracking secondary and temporary objects would thus be added veracity and detail to earned value calculations, and subsequently better project control and performance. The paper aims to discuss these issues.

Design/methodology/approach

Two techniques for recognizing concrete construction secondary and temporary objects in TLS point clouds are implemented and tested using real-life data collected from a reinforced concrete building construction site. Both techniques represent significant innovative extensions of existing “Scan-vs-BIM” object recognition frameworks.

Findings

The experimental results show that it is feasible to recognise secondary and temporary objects in TLS point clouds with good accuracy using the two novel techniques; but it is envisaged that superior results could be achieved by using additional cues such as colour and 3D edge information.

Originality/value

This article makes valuable contributions to the problem of detecting and tracking secondary and temporary objects in 3D point clouds. The power of Scan-vs-BIM object recognition approaches to address this problem is demonstrated, but their limitations are also highlighted.

Details

Construction Innovation, vol. 14 no. 2
Type: Research Article
ISSN: 1471-4175

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 results…

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

Article
Publication date: 11 October 2021

Carlos J.L. Balsas

Societal problems have impacted the northeast of the USA for various generations. This paper aims to analyse various sustainability aspects in the Hudson River watershed of New…

Abstract

Purpose

Societal problems have impacted the northeast of the USA for various generations. This paper aims to analyse various sustainability aspects in the Hudson River watershed of New York by highlighting a temporal progression from environmental sustainability at the watershed level in the 1970s to growing concerns with more localized cross-border social and cultural sustainability in recent decades. We discuss an engagement with the Rapp Road Historic District and a documentary screening series as potential ways to eliminate racism and embrace diversity.

Design/methodology/approach

The research was based on fieldwork and classroom teaching conducted mostly since summer 2014. It included mixed methods combining document analysis and reviews with the examination of case studies, and the assessment of public policy priorities.

Findings

Formal training has to be combined with a substantial dose of realism, humility and motivation to recognize that what the authors teach and research in the community matters. Future learning experiences within a place-based education paradigm could include: Having students help devise urban rehabilitation strategies whilst suggesting integrative measures with the surrounding built and natural environments; students could also help improve public spaces in the neighbourhood; and finally, they could also help to strengthen the cultural identity of the district by augmenting urban design features endogenous to the African American community.

Practical implications

Opportunities could be further augmented with service-learning projects and programmes, internships and even full-time jobs for recent graduates in local community development organizations.

Social implications

The study served to raise the community’s awareness of its own natural, ecological and human assets, and to create place-based real-world opportunities for students and faculty in environmental and cultural sustainability studies.

Originality/value

Environmental sustainability is discussed with the creation of the Hudson River Valley National Heritage Area, whilst the public engagement with the Rapp Road Historic Association in the Capital Region of upstate New York, the identification of an emerging creative cluster in the Berkshires-Hudson region, and a documentary and discussion series on striving for diverse cities serve to demonstrate current concerns with social and cultural sustainability.

Details

Journal of Place Management and Development, vol. 15 no. 3
Type: Research Article
ISSN: 1753-8335

Keywords

Article
Publication date: 2 November 2012

Pradeep K. Rawat, Prakash C. Tiwari and Charu C. Pant

The purpose of the study is to assess the environmental and socio‐economic impacts and risks of climate change through GIS database management system (DBMS) on land…

Abstract

Purpose

The purpose of the study is to assess the environmental and socio‐economic impacts and risks of climate change through GIS database management system (DBMS) on land use‐informatics and climate‐informatics. The Dabka watershed constitutes a part of the Kosi Basin in the Lesser Himalaya, India in district Nainital has been selected for the case illustration.

Design/methodology/approach

Land use‐informatics consists of land use mapping and change diction, i.e. decadal changes and annual changes. Climate‐informatics consists of climate change detection through daily, monthly and annual weather data for a period of 25 years.

Findings

The exercise revealed that oak and pine forests have decreased, respectively, by 25 percent (4.48 km2) and 3 percent (0.28 km2) thus bringing a decline of 4.76 km2 forest in the watershed during 1990 to 2010. But, due to climate change the mixed forest taking place of oak forest in certain pockets and consequently the mixed forest in the catchment increased by 18 percent (2.3 km2) during the same period which reduced the overall loss of forests in the region but its not eco‐friendly as the oak forest. Barren land increased 1.21 km2 (56 percent), riverbed increased 0.78 km2 (52 percent) and cultivated land increased about 0.63 km2 (3 percent) during the period of 1990 to 2010. Out of the total seven classes of the land use land cover, five classes (i.e. Oak, Pine, Mixed, Barren and Riverbed) are being changed dominantly due to climate change factor and anthropogenic factors plays a supporting role whereas only two classes (scrub land and agricultural land) are being changed dominantly by anthropogenic factors and climate change factors plays a supporting role. Expansion of mixed forest land brought out due to upslope shifting of existing forest species due to climate change factor only because upslope areas getting warmer than past with the rate of 9°C‐12°C/two decades. Consequently, the results concluded that the high rate of land use change accelerating several environmental problems such as high runoff, flash flood, river‐line flood and soil erosion during monsoon season and drought during non‐monsoon period. These environmental problems cause great loss to life and property and poses serious threat to the process of development with have far‐reaching economic and social consequences.

Originality/value

This study generated primary data on land use‐informatics and climate‐informatics to integrate each‐other for impact assessment and mitigation through sustainable land use as constitutes a part of a multidisciplinary project, Department of Science and Technology (D.S.T.) Government of India.

Details

International Journal of Climate Change Strategies and Management, vol. 4 no. 4
Type: Research Article
ISSN: 1756-8692

Keywords

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