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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: 26 January 2010

Padmapriya Nammalwar, Ovidiu Ghita and Paul F. Whelan

The purpose of this paper is to propose a generic framework based on the colour and the texture features for colour‐textured image segmentation. The framework can be…

Abstract

Purpose

The purpose of this paper is to propose a generic framework based on the colour and the texture features for colour‐textured image segmentation. The framework can be applied to any real‐world applications for appropriate interpretation.

Design/methodology/approach

The framework derives the contributions of colour and texture in image segmentation. Local binary pattern and an unsupervised k‐means clustering are used to cluster pixels in the chrominance plane. An unsupervised segmentation method is adopted. A quantitative estimation of colour and texture performance in segmentation is presented. The proposed method is tested using different mosaic and natural images and other image database used in computer vision. The framework is applied to three different applications namely, Irish script on screen images, skin cancer images and sediment profile imagery to demonstrate the robustness of the framework.

Findings

The inclusion of colour and texture as distributions of regions provided a good discrimination of the colour and the texture. The results indicate that the incorporation of colour information enhanced the texture analysis techniques and the methodology proved effective and efficient.

Originality/value

The novelty lies in the development of a generic framework using both colour and texture features for image segmentation and the different applications from various fields.

Details

Sensor Review, vol. 30 no. 1
Type: Research Article
ISSN: 0260-2288

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Article
Publication date: 1 April 1986

J.F. Stelzer

The application of colour for an improved presentation of 3‐D structures with finite elements is reported. Also shown is how the hidden‐surface technique can be used for…

Abstract

The application of colour for an improved presentation of 3‐D structures with finite elements is reported. Also shown is how the hidden‐surface technique can be used for: (1) generating pictures in the hidden line alike mode, (2) generating photo‐alike pictures by shading the surfaces according to Lambert's cosine law, (3) showing the regions of different materials or properties by distinct colouring, (4) the presentation of temperature and stress fields by colouring. This colouring is done with smooth colour transitions and delivers pictures similar to those gained by thermography or stress optics. Furthermore, (5) it is possible to generate contour lines on the remaining visible surfaces. The problems arising with the attachment of a colour hardcopier are also considered.

Details

Engineering Computations, vol. 3 no. 4
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 22 August 2017

Jiangping Yuan, Zhaohui Yu, Guangxue Chen, Ming Zhu and Yanfei Gao

The purpose of this paper is to study a feasible visualization of large-size three-dimension (3D) color models which are beyond the maximum print size of newest…

Abstract

Purpose

The purpose of this paper is to study a feasible visualization of large-size three-dimension (3D) color models which are beyond the maximum print size of newest paper-based 3D printer used 3D cutting-bonding frame (3D-CBF) and evaluate the effects of cutting angle and layout method on printing time of designed models.

Design/methodology/approach

Sixteen models, including cuboid model, cylinder model, hole model and sphere model with different shape features, were divided into two symmetric parts and printed by the Mcor IRIS HD 3D printer. Before printing, two sub-parts were rearranged in one of three layout methods. Nine scaled sizes of original models were printed to find the quantitative relationship between printing time and scale values in each type. For the 0.3 times of original models, six cutting angles were evaluated in detail.

Findings

The correlation function about colorization time and printed pages was proposed. Based on 3D-CBF, the correlation between printing time and scale size is statistically defined. Optimization parameters of designed parts visualization about cutting angel and layout method were found, even if their statistical results were difficult to model their effects on printing time of specimens.

Research limitations/implications

The research is comparative and limited to the special models and used procedures.

Originality/value

The paper provides a feasible visualization and printing speed optimization methods for the further industrialization of 3D paper-based printing technology in cultural creative field.

Details

Rapid Prototyping Journal, vol. 23 no. 5
Type: Research Article
ISSN: 1355-2546

Keywords

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Article
Publication date: 28 August 2019

Linlin Bai and Jiu Zhou

The purpose of this paper, on innovative design of traditional weft-backed woven fabric, is to investigate a design principle and method for full-backed structure with…

Abstract

Purpose

The purpose of this paper, on innovative design of traditional weft-backed woven fabric, is to investigate a design principle and method for full-backed structure with double-faced shading effect to realize two types of double-faced shading effects for traditional weft-backed fabric that are impossible to be realized under plane design mode. In addition, the study on the color rendering law is conducive to the design application, and the effectiveness of the design method has been verified by the design practices.

Design/methodology/approach

This paper presents a design method for full-backed structure with two shaded weave databases (SWDs) by selecting two primary weaves (PWs), establishing the corresponding SWDs, selecting the proper compound structures for database of full-backed structure with double-faced shading effect. Color card fabric with 544 specimens is produced and their color values are measured, their color difference and variance are analyzed to evaluate the color rendering characteristics. Finally, double-faced weft-backed fabrics are produced under layered-combination design mode to verify the practicality of full-backed structure with double-faced shading effect.

Findings

Weft-backed woven fabrics with “SPDC” (same pattern and different color) and “DPDC” (different pattern and different color) shading effects can be produced using full-backed structure with double-faced shading effect. The color expression is extremely enhanced (136 compound structures on one side for one color weft). In the shading process, two sets of wefts do not affect each other, and stable and ideal color shading effect with high color purity can be expressed according to the analyses on the L* (lightness) values, color purity, color differences (0.47–3.20) and variance (0.25–1.21) of the color card fabric.

Originality/value

Breaking through the structural limitations and achieving the double-faced shading effects that cannot be expressed in plane design mode. The research on two weft-backed fabric with the most basic weft-backed structure provides not only a theoretical base for further study on weft-backed structures, but also some references for structure innovation design of traditional weft-backed woven fabrics.

Details

International Journal of Clothing Science and Technology, vol. 32 no. 2
Type: Research Article
ISSN: 0955-6222

Keywords

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Article
Publication date: 4 April 2016

Babar Khan, Fang Han, Zhijie Wang and Rana J. Masood

This paper aims to propose a biologically inspired processing architecture to recognize and classify fabrics with respect to the weave pattern (fabric texture) and yarn…

Abstract

Purpose

This paper aims to propose a biologically inspired processing architecture to recognize and classify fabrics with respect to the weave pattern (fabric texture) and yarn color (fabric color).

Design/methodology/approach

By using the fabric weave patterns image identification system, this study analyzed the fabric image based on the Hierarchical-MAX (HMAX) model of computer vision, to extract feature values related to texture of fabric. Red Green Blue (RGB) color descriptor based on opponent color channels simulating the single opponent and double opponent neuronal function of the brain is incorporated in to the texture descriptor to extract yarn color feature values. Finally, support vector machine classifier is used to train and test the algorithm.

Findings

This two-stage processing architecture can be used to construct a system based on computer vision to recognize fabric texture and to increase the system reliability and accuracy. Using this method, the stability and fault tolerance (invariance) was improved.

Originality/value

Traditionally, fabric texture recognition is performed manually by visual inspection. Recent studies have proposed automatic fabric texture identification based on computer vision. In the identification process, the fabric weave patterns are recognized by the warp and weft floats. However, due to the optical environments and the appearance differences of fabric and yarn, the stability and fault tolerance (invariance) of the computer vision method are yet to be improved. By using our method, the stability and fault tolerance (invariance) was improved.

Details

Assembly Automation, vol. 36 no. 2
Type: Research Article
ISSN: 0144-5154

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Article
Publication date: 23 August 2019

Shenlong Wang, Kaixin Han and Jiafeng Jin

In the past few decades, the content-based image retrieval (CBIR), which focuses on the exploration of image feature extraction methods, has been widely investigated. The…

Abstract

Purpose

In the past few decades, the content-based image retrieval (CBIR), which focuses on the exploration of image feature extraction methods, has been widely investigated. The term of feature extraction is used in two cases: application-based feature expression and mathematical approaches for dimensionality reduction. Feature expression is a technique of describing the image color, texture and shape information with feature descriptors; thus, obtaining effective image features expression is the key to extracting high-level semantic information. However, most of the previous studies regarding image feature extraction and expression methods in the CBIR have not performed systematic research. This paper aims to introduce the basic image low-level feature expression techniques for color, texture and shape features that have been developed in recent years.

Design/methodology/approach

First, this review outlines the development process and expounds the principle of various image feature extraction methods, such as color, texture and shape feature expression. Second, some of the most commonly used image low-level expression algorithms are implemented, and the benefits and drawbacks are summarized. Third, the effectiveness of the global and local features in image retrieval, including some classical models and their illustrations provided by part of our experiment, are analyzed. Fourth, the sparse representation and similarity measurement methods are introduced, and the retrieval performance of statistical methods is evaluated and compared.

Findings

The core of this survey is to review the state of the image low-level expression methods and study the pros and cons of each method, their applicable occasions and certain implementation measures. This review notes that image peculiarities of single-feature descriptions may lead to unsatisfactory image retrieval capabilities, which have significant singularity and considerable limitations and challenges in the CBIR.

Originality/value

A comprehensive review of the latest developments in image retrieval using low-level feature expression techniques is provided in this paper. This review not only introduces the major approaches for image low-level feature expression but also supplies a pertinent reference for those engaging in research regarding image feature extraction.

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Article
Publication date: 1 June 2021

Merrin Prasanna Nagadasari and Polaiah Bojja

A rotary kiln is a pyro processing device that is used to raise the temperature of materials in cement factories. Temperature monitoring is an essential process in the…

Abstract

Purpose

A rotary kiln is a pyro processing device that is used to raise the temperature of materials in cement factories. Temperature monitoring is an essential process in the rotary kiln to yield high quality clinker. Temperature measurement is a challenging task in clinkering process and it is difficult to apply automation techniques. As the pyrometer gives unreliable readings, it is necessary to apply various image processing techniques on the camera images to measure the temperature inside the kiln at different zones.

Design/methodology/approach

In this paper, a fuzzy logic rule-based analysis is proposed to measure temperature using a burning flame image in which it considers red, green, blue (RGB) magnitude planes. The proposed method uses Mamdani fuzzy inference system for decision-making. The system takes RGB magnitude as an input fuzzified variable and generates temperature as fuzzified output.

Findings

This paper focuses on the temperature measurement obtained from the images of the camera system. The commands to the valves and actuators are controlled using the center of gravity of the control regime. The fuzzy logic controller detects the temperature of flame zones using color features of burning flame images.

Originality/value

Precise temperature mapping of flame images helps to control the temperature inside the rotating kiln to produce high quality clinker. The process can be viewed remotely and controlled using various control loops from anywhere.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

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Article
Publication date: 10 August 2010

In Hwan Sul and Tae Jin Kang

The purpose of this paper is to find automatic post‐processing scheme to give textures and motion data to three dimensional (3D) body scan data.

Abstract

Purpose

The purpose of this paper is to find automatic post‐processing scheme to give textures and motion data to three dimensional (3D) body scan data.

Design/methodology/approach

Semi‐implicit particle‐based method was applied to post‐processing of 3D body scan data. The template avatar mesh was draped onto the target scan data and the texture/motion data were transferred to regenerated body. Automatic body feature detection was used to correlate the template body with the target body.

Findings

Using semi‐implicit particle method, there are advantages in both computational stability and accuracy. The calculation is done in a few minutes and even data with many holes could be used.

Originality/value

There are several researches for body feature detection and scan body regeneration but this paper aims for fully automatic method which needs no human intervention. The semi‐implicit particle method, which is popularly used for cloth simulation, is applied to body data regeneration. The conventional 3D body scan data, which had no colors and motions can be given textures and motions with this approach. And even the face can be freely interchanged with the use of external face generation software.

Details

International Journal of Clothing Science and Technology, vol. 22 no. 4
Type: Research Article
ISSN: 0955-6222

Keywords

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Article
Publication date: 29 November 2018

Shankar Chakraborty, Rajeev Ranjan and Poulomi Mondal

A road network provides arterial arrangement to facilitate business, transport, social integration and economic progress of any nation. During the last seven decades after…

Abstract

Purpose

A road network provides arterial arrangement to facilitate business, transport, social integration and economic progress of any nation. During the last seven decades after independence, road transport infrastructure in India has expanded manifold, both in terms of spread (total length and density of road) and capacity (number of on-road registered vehicles, and volume of passenger and freight traffic handled). But, with the enrichment of road transport network in India, the number of traffic accidents and total cost for maintaining the road infrastructure also keeps on increasing. It becomes necessary to evaluate state-wise performance of the Indian roads using some mathematical tools. The paper aims to discuss this issue.

Design/methodology/approach

In this paper, using preference ranking organization method for enrichment of evaluations (PROMETHEE) and geometrical analysis for interactive aid (GAIA) approaches, an attempt is made to appraise the state-wise performance of Indian roads based on 12 critically important criteria. A geographic information system method and a hue-saturation-value color coding scheme are also employed to identify the influence of individual criterion on the overall rank of 29 Indian states.

Findings

It is observed that amongst all the considered states, the road conditions in the states of Mizoram and Arunachal Pradesh are really satisfactory, whereas Bihar and Uttar Pradesh are the lagging states requiring governmental intervention and support to enhance their road network infrastructure.

Practical implications

This analysis would help the decision makers to identify the strengths and deficiencies of each Indian state with respect to its road conditions so that proper promotional and growth actions can be implemented.

Originality/value

From the review of the existing literature, it is quite evident that till date, no research work has been conducted in order to evaluate the performance of roads, and their conditions and characteristic features in the Indian context. In this paper, the state-wise performance of the Indian roads is appraised based on several identified parameters using a combined PROMETHEE-GAIA approach.

Details

Benchmarking: An International Journal, vol. 25 no. 9
Type: Research Article
ISSN: 1463-5771

Keywords

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