Search results

1 – 10 of over 1000
Article
Publication date: 13 September 2011

Cheng Zhong, Hui Li and Xianfeng Huang

Orthophoto suffers from the relief displacement effects magnified by high resolution imaging sensors especially when mapping urban areas. True orthophotos eliminating…

Abstract

Purpose

Orthophoto suffers from the relief displacement effects magnified by high resolution imaging sensors especially when mapping urban areas. True orthophotos eliminating relief displacement with digital surface model (DSM) are presented to assure reliable interpretability and maintain the high quality of the available data. Previous efforts did not provide accurate and fast ways for generating true othorphoto. The purpose of this paper is to try to solve the problem by analyzing the complexity of algorithm processes and finding the optimum manner to allocate them.

Design/methodology/approach

In this paper, an optimum segmentation number for radial sweep is presented to achieve minimum complexity. First, the scan area, number of azimuth lines and visibility judgment area of radial sweep and spiral sweep method have been discussed with rigorous geometric theory, and then algorithm complexities of both methods are estimated with mathematical computation theory. Finally, minimum complexity of the methods is obtained with extreme point theory of differential calculus.

Findings

Experiments have demonstrated that the proposed method has the best efficiency, and is efficient to avoid “M‐potion” problem, and false occlusions and false visibilities caused by the rolling area, the incompatibility between the DSM and ground image resolution.

Originality/value

The deduction and experiments indicate that the proposed method is a robust, accurate, fast, and effective approach to generate high quality, true orthophoto at a large‐scale.

Article
Publication date: 6 February 2017

Zhongyi Wang, Jin Zhang and Jing Huang

Current segmentation systems almost invariably focus on linear segmentation and can only divide text into linear sequences of segments. This suits cohesive text such as…

Abstract

Purpose

Current segmentation systems almost invariably focus on linear segmentation and can only divide text into linear sequences of segments. This suits cohesive text such as news feed but not coherent texts such as documents of a digital library which have hierarchical structures. To overcome the focus on linear segmentation in document segmentation and to realize the purpose of hierarchical segmentation for a digital library’s structured resources, this paper aimed to propose a new multi-granularity hierarchical topic-based segmentation system (MHTSS) to decide section breaks.

Design/methodology/approach

MHTSS adopts up-down segmentation strategy to divide a structured, digital library document into a document segmentation tree. Specifically, it works in a three-stage process, such as document parsing, coarse segmentation based on document access structures and fine-grained segmentation based on lexical cohesion.

Findings

This paper analyzed limitations of document segmentation methods for the structured, digital library resources. Authors found that the combination of document access structures and lexical cohesion techniques should complement each other and allow for a better segmentation of structured, digital library resources. Based on this finding, this paper proposed the MHTSS for the structured, digital library resources. To evaluate it, MHTSS was compared to the TT and C99 algorithms on real-world digital library corpora. Through comparison, it was found that the MHTSS achieves top overall performance.

Practical implications

With MHTSS, digital library users can get their relevant information directly in segments instead of receiving the whole document. This will improve retrieval performance as well as dramatically reduce information overload.

Originality/value

This paper proposed MHTSS for the structured, digital library resources, which combines the document access structures and lexical cohesion techniques to decide section breaks. With this system, end-users can access a document by sections through a document structure tree.

Article
Publication date: 4 December 2020

Fang-Jye Shiue, Hsin-Yun Lee, Meng-Cong Zheng, Akhmad F.K. Khitam and Sintayehu Assefa

For large projects, project segmentation and planning the size of contract packages in construction bids is a complex and critical issue. Due to the nature of construction…

382

Abstract

Purpose

For large projects, project segmentation and planning the size of contract packages in construction bids is a complex and critical issue. Due to the nature of construction projects, which frequently have large budgets, long durations and many activities with complex procedures, project segmentation involves complicated decision-making. To fill this gap, this study aims to develop an integrated model for planning project segmentation.

Design/methodology/approach

The proposed model integrates a simulation and multiple attribute decision-making method. The simulation is used to evaluate the bidding outcome of various project segmentations. The owner can then determine the bid-price behavior of contractors in response to varying work package sizes. The multiple attribute decision-making method is used to select the optimal segmentation solution from the simulated scenarios.

Findings

The proposed model is applied to a large road preservation project in Indonesia and incorporates bid participants and market conditions. The model provides seven scenarios for segmentation. The range of scenarios captures increasing competitiveness in the construction with the average bid price becoming gradually more beneficial for the owner. The model also utilizes a multiple attribute decision-making method to select the optimum scenario for the owner.

Originality/value

This study presents an applicable model for project segmentation that is useful for both project owners and contractors. By utilizing the proposed model, a project owner can segment a large project into smaller contract packages to create improved project pricing.

Details

Engineering, Construction and Architectural Management, vol. 28 no. 9
Type: Research Article
ISSN: 0969-9988

Keywords

Open Access
Article
Publication date: 15 December 2020

Soha Rawas and Ali El-Zaart

Image segmentation is one of the most essential tasks in image processing applications. It is a valuable tool in many oriented applications such as health-care systems…

Abstract

Purpose

Image segmentation is one of the most essential tasks in image processing applications. It is a valuable tool in many oriented applications such as health-care systems, pattern recognition, traffic control, surveillance systems, etc. However, an accurate segmentation is a critical task since finding a correct model that fits a different type of image processing application is a persistent problem. This paper develops a novel segmentation model that aims to be a unified model using any kind of image processing application. The proposed precise and parallel segmentation model (PPSM) combines the three benchmark distribution thresholding techniques to estimate an optimum threshold value that leads to optimum extraction of the segmented region: Gaussian, lognormal and gamma distributions. Moreover, a parallel boosting algorithm is proposed to improve the performance of the developed segmentation algorithm and minimize its computational cost. To evaluate the effectiveness of the proposed PPSM, different benchmark data sets for image segmentation are used such as Planet Hunters 2 (PH2), the International Skin Imaging Collaboration (ISIC), Microsoft Research in Cambridge (MSRC), the Berkley Segmentation Benchmark Data set (BSDS) and Common Objects in COntext (COCO). The obtained results indicate the efficacy of the proposed model in achieving high accuracy with significant processing time reduction compared to other segmentation models and using different types and fields of benchmarking data sets.

Design/methodology/approach

The proposed PPSM combines the three benchmark distribution thresholding techniques to estimate an optimum threshold value that leads to optimum extraction of the segmented region: Gaussian, lognormal and gamma distributions.

Findings

On the basis of the achieved results, it can be observed that the proposed PPSM–minimum cross-entropy thresholding (PPSM–MCET)-based segmentation model is a robust, accurate and highly consistent method with high-performance ability.

Originality/value

A novel hybrid segmentation model is constructed exploiting a combination of Gaussian, gamma and lognormal distributions using MCET. Moreover, and to provide an accurate and high-performance thresholding with minimum computational cost, the proposed PPSM uses a parallel processing method to minimize the computational effort in MCET computing. The proposed model might be used as a valuable tool in many oriented applications such as health-care systems, pattern recognition, traffic control, surveillance systems, etc.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Article
Publication date: 22 March 2013

Wenping Ma, Feifei Ti, Congling Li and Licheng Jiao

The purpose of this paper is to present a Differential Immune Clone Clustering Algorithm (DICCA) to solve image segmentation.

Abstract

Purpose

The purpose of this paper is to present a Differential Immune Clone Clustering Algorithm (DICCA) to solve image segmentation.

Design/methodology/approach

DICCA combines immune clone selection and differential evolution, and two populations are used in the evolutionary process. Clone reproduction and selection, differential mutation, crossover and selection are adopted to evolve two populations, which can increase population diversity and avoid local optimum. After extracting the texture features of an image and encoding them with real numbers, DICCA is used to partition these features, and the final segmentation result is obtained.

Findings

This approach is applied to segment all sorts of images into homogeneous regions, including artificial synthetic texture images, natural images and remote sensing images, and the experimental results show the effectiveness of the proposed algorithm.

Originality/value

The method presented in this paper represents a new approach to solving clustering problems. The novel method applies the idea two populations are used in the evolutionary process. The proposed clustering algorithm is shown to be effective in solving image segmentation.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 6 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 30 July 2019

Mehdi Kazemi and Abdolreza Rahimi

Additive manufacturing technology significantly simplifies the production of complex three-dimensional (3 D) parts directly from the computer-aided design (CAD) model…

Abstract

Purpose

Additive manufacturing technology significantly simplifies the production of complex three-dimensional (3 D) parts directly from the computer-aided design (CAD) model. Although additive manufacturing (AM) processes have unexampled flexibility, they still have restrictions inhibiting engineers to easily generate some specific geometric shapes, easily. Some of these problems pertain to the consumption of materials as supports, the inferior surface finish of some surfaces with certain angles, etc. One of the approaches to overcome these problems is designing by segmentation.

Design/methodology/approach

The proposed methodology consists of two steps: (1) segmentation of the 3 D model and (2) exploring the best orientation for each segment. In the first step, engineers consider the possible number of segments and the connection method of segments. In this paper, a series of segments, called a segmentation pattern (SP), is obtained by the recognition of features and separating them automatically (or manually when needed) with one or more appropriate planes. In the second step, the best fabrication orientation should be chosen. The criteria for choosing the best SP and OPs are minimizing the support volume, building time (directly affected by segments’ height in layer-wise AM processes) and surface roughness. Both steps are performed automatically (or manually when needed) by the algorithm created based on principles of particle swarm optimization (PSO) algorithm using Visual C#.

Findings

Experimental tests show that the segmentation design improves AM processes from the aspects of building time, material consumption and the surface quality. Segmentation design empowers users of AM technologies to reduce consumption of material by decreasing the support structures, to decrease the time of building by lowering the segments height and to decrease the surface roughness.

Originality/value

This paper presents an original approach in efficiency improvement of AM technologies, thus bringing the AM one step closer to maturity.

Details

Rapid Prototyping Journal, vol. 25 no. 7
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 8 June 2012

Mohammad Vaezi, Chee Kai Chua and Siaw Meng Chou

Today, medical models can be made by the use of medical imaging systems through modern image processing methods and rapid prototyping (RP) technology. In ultrasound…

1203

Abstract

Purpose

Today, medical models can be made by the use of medical imaging systems through modern image processing methods and rapid prototyping (RP) technology. In ultrasound imaging systems, as images are not layered and are of lower quality as compared to those of computerized tomography (CT) and magnetic resonance imaging (MRI), the process for making physical models requires a series of intermediate processes and it is a challenge to fabricate a model using ultrasound images due to the inherent limitations of the ultrasound imaging process. The purpose of this paper is to make high quality, physical models from medical ultrasound images by combining modern image processing methods and RP technology.

Design/methodology/approach

A novel and effective semi‐automatic method was developed to improve the quality of 2D image segmentation process. In this new method, a partial histogram of 2D images was used and ideal boundaries were obtained. A 3D model was achieved using the exact boundaries and then the 3D model was converted into the stereolithography (STL) format, suitable for RP fabrication. As a case study, the foetus was chosen for this application since ultrasonic imaging is commonly used for foetus imaging so as not to harm the baby. Finally, the 3D Printing (3DP) and PolyJet processes, two types of RP technique, were used to fabricate the 3D physical models.

Findings

The physical models made in this way proved to have sufficient quality and shortened the process time considerably.

Originality/value

It is still a challenge to fabricate an exact physical model using ultrasound images. Current commercial histogram‐based segmentation method is time‐consuming and results in a less than optimum 3D model quality. In this research work, a novel and effective semi‐automatic method was developed to select the threshold optimum value easily.

Details

Rapid Prototyping Journal, vol. 18 no. 4
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 9 August 2011

William J. McCluskey and Richard A. Borst

The purpose of this paper is to describe a segmentation technique based on geostatistical modeling methods utilizing geographically weighted regression (GWR) to identify…

Abstract

Purpose

The purpose of this paper is to describe a segmentation technique based on geostatistical modeling methods utilizing geographically weighted regression (GWR) to identify submarkets which could be applied within the mass appraisal environment.

Design/methodology/approach

Given the spatial dimension within which neighbourhoods/submarkets exist, this paper has sought to utilize the geostatistical technique of GWR to identify them.

Findings

The efficacy of the procedure is established by demonstrating improvements in predictive accuracy of the resultant segmented market models as compared to a baseline global unsegmented model for each of the study areas. Optimal number of segments is obtained by measures of predictive accuracy, spatial autocorrelation in the residual errors and the Akaike information criterion.

Research limitations/implications

The three datasets used allowed for an evaluation of the robustness of the method. Nonetheless it would be beneficial to test it on other datasets, particularly from different regions of the world.

Practical implications

Many researchers and mass appraisal practitioners have established the benefit of segmenting a study area into two or more submarkets as a means of incorporating the effects of location within mass valuation models. This approach develops the existing knowledge.

Social implications

The research ultimately is developing more accurate valuation models upon which the property tax is based. This should create an environment of fair and acceptable assessed values by the tax paying community.

Originality/value

The contribution of this work lies in the methodological approach adopted which incorporates a market basket approach developed through a process of GWR. The importance of the research findings illustrate that submarket segmentation need no longer be an arbitrary process.

Details

International Journal of Housing Markets and Analysis, vol. 4 no. 3
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 1 February 1990

Gordon Wills, Sherril H. Kennedy, John Cheese and Angela Rushton

To achieve a full understanding of the role ofmarketing from plan to profit requires a knowledgeof the basic building blocks. This textbookintroduces the key concepts in…

13576

Abstract

To achieve a full understanding of the role of marketing from plan to profit requires a knowledge of the basic building blocks. This textbook introduces the key concepts in the art or science of marketing to practising managers. Understanding your customers and consumers, the 4 Ps (Product, Place, Price and Promotion) provides the basic tools for effective marketing. Deploying your resources and informing your managerial decision making is dealt with in Unit VII introducing marketing intelligence, competition, budgeting and organisational issues. The logical conclusion of this effort is achieving sales and the particular techniques involved are explored in the final section.

Details

Management Decision, vol. 28 no. 2
Type: Research Article
ISSN: 0025-1747

Keywords

Article
Publication date: 1 February 2016

C.H. Wu, G.T.S. Ho, C.H.Y. Lam, W.H. Ip, K.L. Choy and Y.K. Tse

The purpose of this paper is to present a novel approach for niche-market tour identification, with the objective to obtain a better segmentation of target tourists and…

2214

Abstract

Purpose

The purpose of this paper is to present a novel approach for niche-market tour identification, with the objective to obtain a better segmentation of target tourists and support the design of tourism products. A proposed system, namely the Niche Tourism Identification System (NTIS) was implemented based on the proposed scheme and its functionality was showcased in a case study undertaken with a local travel agency.

Design/methodology/approach

The proposed system implements automated customer market segmentation, based on similar characteristics that can be collected from potential customers. After that, special-interest tourism-based market strategies and products can be designed for the potential customers. The market segmentation is conducted using a GA-based k-means clustering engine (GACE), while the parameter setting is controlled by the travel agents.

Findings

The proposed NTIS was deployed in a real-world case study which helps a local travel agency to determine the various types of niche tourism found in the existing market in Hong Kong. Its output was reviewed by experience tour planners. It was found that with the niche characteristics can be successfully revealed by summarizing the possible factors within the potential clusters in the existing database. The system performed consistently compared to human planners.

Originality/value

To the best of the authors’ knowledge, although some alternative methods for segmenting travel markets have been proposed, few have provided any effective approaches for identifying existing niche markets to support online inquiry. Also, GACE has been proposed to compensate for the limitations that challenge k-means clustering in binding to a local optimum and for its weakness in dealing with multi-dimensional space.

1 – 10 of over 1000