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Article
Publication date: 17 September 2019

Chérif Taouche and Hacene Belhadef

Palmprint recognition is a very interesting and promising area of research. Much work has already been done in this area, but much more needs to be done to make the…

Abstract

Purpose

Palmprint recognition is a very interesting and promising area of research. Much work has already been done in this area, but much more needs to be done to make the systems more efficient. In this paper, a multimodal biometrics system based on fusion of left and right palmprints of a person is proposed to overcome limitations of unimodal systems.

Design/methodology/approach

Features are extracted using some proposed multi-block local descriptors in addition to MBLBP. Fusion of extracted features is done at feature level by a simple concatenation of feature vectors. Then, feature selection is performed on the resulting global feature vector using evolutionary algorithms such as genetic algorithms and backtracking search algorithm for a comparison purpose. The benefits of such step selecting the relevant features are known in the literature, such as increasing the recognition accuracy and reducing the feature set size, which results in runtime saving. In matching step, Chi-square similarity measure is used.

Findings

The resulting feature vector length representing a person is compact and the runtime is reduced.

Originality/value

Intensive experiments were done on the publicly available IITD database. Experimental results show a recognition accuracy of 99.17 which prove the effectiveness and robustness of the proposed multimodal biometrics system than other unimodal and multimodal biometrics systems.

Details

Information Discovery and Delivery, vol. 48 no. 1
Type: Research Article
ISSN: 2398-6247

Keywords

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Article
Publication date: 16 January 2017

Shervan Fekriershad and Farshad Tajeripour

The purpose of this paper is to propose a color-texture classification approach which uses color sensor information and texture features jointly. High accuracy, low noise

Abstract

Purpose

The purpose of this paper is to propose a color-texture classification approach which uses color sensor information and texture features jointly. High accuracy, low noise sensitivity and low computational complexity are specified aims for this proposed approach.

Design/methodology/approach

One of the efficient texture analysis operations is local binary patterns (LBP). The proposed approach includes two steps. First, a noise resistant version of color LBP is proposed to decrease its sensitivity to noise. This step is evaluated based on combination of color sensor information using AND operation. In a second step, a significant points selection algorithm is proposed to select significant LBPs. This phase decreases final computational complexity along with increasing accuracy rate.

Findings

The proposed approach is evaluated using Vistex, Outex and KTH-TIPS-2a data sets. This approach has been compared with some state-of-the-art methods. It is experimentally demonstrated that the proposed approach achieves the highest accuracy. In two other experiments, results show low noise sensitivity and low computational complexity of the proposed approach in comparison with previous versions of LBP. Rotation invariant, multi-resolution and general usability are other advantages of our proposed approach.

Originality/value

In the present paper, a new version of LBP is proposed originally, which is called hybrid color local binary patterns (HCLBP). HCLBP can be used in many image processing applications to extract color/texture features jointly. Also, a significant point selection algorithm is proposed for the first time to select key points of images.

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Article
Publication date: 16 August 2019

Neda Tadi Bani and Shervan Fekri-Ershad

Large amount of data are stored in image format. Image retrieval from bulk databases has become a hot research topic. An alternative method for efficient image retrieval…

Abstract

Purpose

Large amount of data are stored in image format. Image retrieval from bulk databases has become a hot research topic. An alternative method for efficient image retrieval is proposed based on a combination of texture and colour information. The main purpose of this paper is to propose a new content based image retrieval approach using combination of color and texture information in spatial and transform domains jointly.

Design/methodology/approach

Various methods are provided for image retrieval, which try to extract the image contents based on texture, colour and shape. The proposed image retrieval method extracts global and local texture and colour information in two spatial and frequency domains. In this way, image is filtered by Gaussian filter, then co-occurrence matrices are made in different directions and the statistical features are extracted. The purpose of this phase is to extract noise-resistant local textures. Then the quantised histogram is produced to extract global colour information in the spatial domain. Also, Gabor filter banks are used to extract local texture features in the frequency domain. After concatenating the extracted features and using the normalised Euclidean criterion, retrieval is performed.

Findings

The performance of the proposed method is evaluated based on the precision, recall and run time measures on the Simplicity database. It is compared with many efficient methods of this field. The comparison results showed that the proposed method provides higher precision than many existing methods.

Originality/value

The comparison results showed that the proposed method provides higher precision than many existing methods. Rotation invariant, scale invariant and low sensitivity to noise are some advantages of the proposed method. The run time of the proposed method is within the usual time frame of algorithms in this domain, which indicates that the proposed method can be used online.

Details

The Electronic Library , vol. 37 no. 4
Type: Research Article
ISSN: 0264-0473

Keywords

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Article
Publication date: 1 September 2000

Ian Stott, David Sanders and Giles Tewkesbury

Describes a new reliable low‐cost ultrasonic ranging system to assist in steering a powered wheelchair. Detection algorithms have been created and implemented on a micro…

Abstract

Describes a new reliable low‐cost ultrasonic ranging system to assist in steering a powered wheelchair. Detection algorithms have been created and implemented on a micro controller based stand‐alone system suitable for a tele‐operated vehicle. The detection uses the gradient of the echo envelope and is resistant to noise and inconsistencies in the detection circuitry. The sensor array was considered as separate sensors, working independently so the system could quickly gather separate sets of range information. These sets were overlaid on to a 2D grid array. The new system is cheaper and simpler than available systems for powered wheelchairs.

Details

Sensor Review, vol. 20 no. 3
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 23 April 2015

A. Azadeh, A. Roohani and S. Motevali Haghighi

This study presents a combined artificial neural network (ANN) and multivariate approach for performance evaluation and optimization of gas refineries. This study…

Abstract

This study presents a combined artificial neural network (ANN) and multivariate approach for performance evaluation and optimization of gas refineries. This study introduces standard financial and non-financial indicators for performance evaluation of the gas refineries. Data are collected from gas balance sheets and the detailed statistics of gas refineries. Two cases have been considered for performance evaluation. In the first case the financial indicators and in the second case the financial and non-financial indicators are used and tested over five years period. The refineries are evaluated by data envelopment analysis (DEA), principal component analysis (PCA), numerical taxonomy and artificial neural network (ANN). Finally, a complete sensitivity analysis is performed for each stated method. The results show that DEA is more resistant to noise than other methods. Also, there is slight difference between results of financial and combined financial and operational indicators. This suggests the use of combined financial and operational indicators for future practical studies in gas refineries. This is the first study that presents an integrated approach for combined performance of financial and operational indicators in gas refineries.

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Article
Publication date: 29 April 2014

Michał Lewandowski and Janusz Walczak

A highly accurate method of current spectrum estimation of a nonlinear load is presented in this paper. Using the method makes it possible to evaluate the current…

Abstract

Purpose

A highly accurate method of current spectrum estimation of a nonlinear load is presented in this paper. Using the method makes it possible to evaluate the current injection frequency domain model of a nonlinear load from previously recorded time domain voltage and current waveforms. The paper aims to discuss these issues.

Design/methodology/approach

The method incorporates the idea of coherent resampling (resampling synchronously with the base frequency of the signal) followed by the discrete Fourier transform (DFT) to obtain the frequency spectrum. When DFT is applied to a synchronously resampled signal, the spectrum is free of negative DFT effects (the spectrum leakage, for example). However, to resample the signal correctly it is necessary to know its base frequency with high accuracy. To estimate the base frequency, the first-order Prony's frequency estimator was used.

Findings

It has been shown that the presented method may lead to superior results in comparison with window interpolated Fourier transform and time-domain quasi-synchronous sampling algorithms.

Research limitations/implications

The method was designed for steady-state analysis in the frequency domain. The voltage and current waveforms across load terminals should be recorded simultaneously to allow correct voltage/current phase shift estimation.

Practical implications

The proposed method can be used in case when the frequency domain model of a nonlinear load is desired and the voltage and current waveforms recorded across load terminals are available. The method leads to correct results even when the voltage/current sampling frequency has not been synchronized with the base frequency of the signal. It can be used for off-line frequency model estimation as well as in real-time DSP systems to restore coherent sampling of the analysed signals.

Originality/value

The method proposed in the paper allows to estimate a nonlinear load frequency domain model from current and voltage waveforms with higher accuracy than other competitive methods, while at the same time its simplicity and computational efficiency is retained.

Details

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 33 no. 3
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 1 August 2016

Jaewoong Lee and InHwan Sul

As an extended work of the previous paper (Sul, 2010), this paper provides a guideline information for an anonymous garment pattern in sewing process. The purpose of this…

Abstract

Purpose

As an extended work of the previous paper (Sul, 2010), this paper provides a guideline information for an anonymous garment pattern in sewing process. The purpose of this paper is to first, provide garment pattern database. By simply taking pictures of garment patterns, the shape database is constructed. Once the shape database is prepared, data retrieval can be done by image indexing, i.e., simply inserting garment pattern boundary shape again to the database. Using shock graph methodology, the pattern sets used for database preparation can be exactly retrieved. Second, to find the nearest shape of a given input pattern shape in the database. If the input garment pattern shape does not exist in the database, the shape matching algorithm provides the next similar pattern data. The user, who is assumed to be non-expert in garment sewing process, can easily predict the position and combination information of various patterns.

Design/methodology/approach

Image processing is used to construct the garment pattern shape database. The boundary shapes are extracted from the photographs of garment patterns and their shape recognition information, especially shock graph, is also recorded for later pattern data retrieval.

Findings

Using the image processing technique, garment patterns can be converted to electronic format easily. Also the prepared pattern database can be used for finding the nearest shape of an additional given input garment pattern. Patterns with irregular shapes were retrieved easily, while those with a simple shape, such as rectangle, showed a little erroneous result.

Originality/value

Shape recognition has been adopted in various industrial areas, except for garment sewing process. Using the provided methodology, garment pattern shapes can be easily saved and retrieved only by taking pictures of them.

Details

International Journal of Clothing Science and Technology, vol. 28 no. 4
Type: Research Article
ISSN: 0955-6222

Keywords

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Article
Publication date: 1 December 1979

JOHN F. COPLIN

The evolution of large fan engines in the late 1960s brought major advances in the technology and operating economics of engines for large transport aircraft. Today…

Abstract

The evolution of large fan engines in the late 1960s brought major advances in the technology and operating economics of engines for large transport aircraft. Today, engines of this type account for well over half the world sales (by value) of commercial aero‐engines.

Details

Aircraft Engineering and Aerospace Technology, vol. 51 no. 12
Type: Research Article
ISSN: 0002-2667

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Article
Publication date: 1 July 2004

Chengdong Wu, Yong Yue, Mengxin Li and Osei Adjei

This paper presents a comprehensive review of the available literature on applications of the rough set theory. Concepts of the rough set theory are discussed for…

Abstract

This paper presents a comprehensive review of the available literature on applications of the rough set theory. Concepts of the rough set theory are discussed for approximation, dependence and reduction of attributes, decision tables and decision rules. The applications of rough sets are discussed in pattern recognition, information processing, business and finance, industry, environment engineering, medical diagnosis and medical data analysis, system fault diagnosis and monitoring and intelligent control systems. Development trends and future efforts are outlined. An extensive list of references is also provided to encourage interested readers to pursue further investigations.

Details

Engineering Computations, vol. 21 no. 5
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 27 July 2012

Anupam Das, J. Maiti and R.N. Banerjee

Monitoring of a process leading to the detection of faults and determination of the root causes are essential for the production of consistent good quality end products…

Abstract

Purpose

Monitoring of a process leading to the detection of faults and determination of the root causes are essential for the production of consistent good quality end products with improved yield. The history of process monitoring fault detection (PMFD) strategies can be traced back to 1930s. Thereafter various tools, techniques and approaches were developed along with their application in diversified fields. The purpose of this paper is to make a review to categorize, describe and compare the various PMFD strategies.

Design/methodology/approach

Taxonomy was developed to categorize PMFD strategies. The basis for the categorization was the type of techniques being employed for devising the PMFD strategies. Further, PMFD strategies were discussed in detail along with emphasis on the areas of applications. Comparative evaluations of the PMFD strategies based on some commonly identified issues were also carried out. A general framework common to all the PMFD has been presented. And lastly a discussion into future scope of research was carried out.

Findings

The techniques employed for PMFD are primarily of three types, namely data driven techniques such as statistical model based and artificial intelligent based techniques, priori knowledge based techniques, and hybrid models, with a huge dominance of the first type. The factors that should be considered in developing a PMFD strategy are ease in development, diagnostic ability, fault detection speed, robustness to noise, generalization capability, and handling of nonlinearity. The review reveals that there is no single strategy that can address all aspects related to process monitoring and fault detection efficiently and there is a need to mesh the different techniques from various PMFD strategies to devise a more efficient PMFD strategy.

Research limitations/implications

The review documents the existing strategies for PMFD with an emphasis on finding out the nature of the strategies, data requirements, model building steps, applicability and scope for amalgamation. The review helps future researchers and practitioners to choose appropriate techniques for PMFD studies for a given situation. Further, future researchers will get a comprehensive but precise report on PMFD strategies available in the literature to date.

Originality/value

The review starts with identifying key indicators of PMFD for review and taxonomy was proposed. An analysis was conducted to identify the pattern of published articles on PMFD followed by evolution of PMFD strategies. Finally, a general framework is given for PMFD strategies for future researchers and practitioners.

Details

International Journal of Quality & Reliability Management, vol. 29 no. 7
Type: Research Article
ISSN: 0265-671X

Keywords

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