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1 – 10 of over 107000
Article
Publication date: 8 July 2022

Uzair Khan, Hikmat Ullah Khan, Saqib Iqbal and Hamza Munir

Image Processing is an emerging field that is used to extract information from images. In recent years, this field has received immense attention from researchers, especially in…

Abstract

Purpose

Image Processing is an emerging field that is used to extract information from images. In recent years, this field has received immense attention from researchers, especially in the research domains of object detection, Biomedical Imaging and Semantic segmentation. In this study, a bibliometric analysis of publications related to image processing in the Science Expanded Index Extended (SCI-Expanded) has been performed. Several parameters have been analyzed such as annual scientific production, citations per article, most cited documents, top 20 articles, most relevant authors, authors evaluation using y-index, top and most relevant sources (journals) and hot topics.

Design/methodology/approach

The Bibliographic data has been extracted from the Web of Science which is well known and the world's top database of bibliographic citations of multidisciplinary areas that covers the various journals of computer science, engineering, medical and social sciences.

Findings

The research work in image processing is meager in the past decade, however, from 2014 to 2019, it increases dramatically. Recently, the IEEE Access journal is the most relevant source with an average of 115 publications per year. The USA is most productive and its publications are highly cited while China comes in second place. Image Segmentation, Feature Extraction and Medical Image Processing are hot topics in recent years. The National Natural Science Foundation of China provides 8% of all funds for Image Processing. As Image Processing is now becoming one of the most critical fields, the research productivity has enhanced during the past five years and more work is done while the era of 2005–2013 was the area with the least amount of work in this area.

Originality/value

This research is novel in this regard that no previous research focuses on Bibliometric Analysis in the Image Processing domain, which is one of the hot research areas in computer science and engineering.

Article
Publication date: 6 February 2019

Sangdo Oh, Sukki Yoon and Patrick Vargas

The purpose of this paper is to investigate consumers’ evaluation of non-focal overlay images appearing closer than the focal point (e.g. a transparent brand logo appearing in…

Abstract

Purpose

The purpose of this paper is to investigate consumers’ evaluation of non-focal overlay images appearing closer than the focal point (e.g. a transparent brand logo appearing in front of an online news article).

Design/methodology/approach

Three experiments identify factors on both task-side and image-side that influence consumers’ liking of non-focal overlay images.

Findings

The findings show that study participants evaluate the non-focal overlay image more favorably when they are engaged in a primary task that is challenging rather than unchallenging, and when the primary task and the non-focal overlay images require different processing modes (e.g. a conceptual primary task paired with a perceptual image) rather than similar processing modes (e.g. a conceptual primary task paired with a conceptual image).

Research limitations/implications

A caveat is that Experiment 1 lacked a baseline condition. Another limitation is that we conducted all three experiments in a controlled laboratory environment, without real-world marketing stimuli. Therefore, further research should be conducted in a field setting to validate how extensively our theoretical insights apply to real-world marketing contexts. Future research may replicate the findings on various platforms such as YouTube and The Wall Street Journal to provide immediate, readily applicable suggestions to online marketers.

Practical implications

The current research provides marketers with a framework for identifying optimal vehicles for the marketing message. Transparent overlay ads can bolster or damage later evaluations of the advertised objects. Online marketers, in their desire to persuade consumers to perceive products positively, must consider what types of activities consumers are pursuing at a target website, what kinds of activities the website promotes and how meaningful are the images.

Originality/value

The current work extends to the work on fluency effects and persuasion knowledge model, both of which have typically shown that subtle exposure to marketing communications positively affects subsequent judgments about products and brands. The findings extend this line of evidence by demonstrating that marketing communications may exert even greater influence when the primary task requires greater cognitive processing.

Details

European Journal of Marketing, vol. 53 no. 2
Type: Research Article
ISSN: 0309-0566

Keywords

Article
Publication date: 4 February 2021

Alena Kostyk and Bruce A. Huhmann

Two studies investigate how different structural properties of images – symmetry (vertical and horizontal) and image contrast – affect social media marketing outcomes of consumer…

2983

Abstract

Purpose

Two studies investigate how different structural properties of images – symmetry (vertical and horizontal) and image contrast – affect social media marketing outcomes of consumer liking and engagement.

Design/methodology/approach

In Study 1’s experiment, 361 participants responded to social media marketing images that varied in vertical or horizontal symmetry and level of image contrast. Study 2 analyzes field data on 610 Instagram posts.

Findings

Study 1 demonstrates that vertical or horizontal symmetry and high image contrast increase consumer liking of social media marketing images, and that processing fluency and aesthetic response mediate these relationships. Study 2 reveals that symmetry and high image contrast improve consumer engagement on social media (number of “likes” and comments).

Research limitations/implications

These studies extend theory regarding processing fluency’s and aesthetic response’s roles in consumer outcomes within social media marketing. Image posts’ structural properties affect processing fluency and aesthetic response without altering brand information or advertising content.

Practical implications

Because consumer liking of marketing communications (e.g. social media posts) predicts persuasion and sales, results should help marketers design more effective posts and achieve brand-building and behavioral objectives. Based on the results, marketers are urged to consider the processing fluency and aesthetic response associated with any image developed for social media marketing.

Originality/value

Addressing the lack of empirical investigations in the existing literature, the reported studies demonstrate that effects of symmetry and image contrast in generating liking are driven by processing fluency and aesthetic response. Additionally, these studies establish novel effects of images’ structural properties on consumer engagement with brand-based social media marketing communications.

Article
Publication date: 27 July 2022

Murat Ayar, Alper Dalkiran, Utku Kale, András Nagy and Tahir Hikmet Karakoc

The use of unmanned aerial vehicles (UAVs) has significantly increased in the past decade and nowadays is being used for various purposes such as image processing, cargo…

Abstract

Purpose

The use of unmanned aerial vehicles (UAVs) has significantly increased in the past decade and nowadays is being used for various purposes such as image processing, cargo transport, archaeology, agriculture, manufacturing, health care, surveillance and inspections. For this reason, using the appropriate image processing method for the intended use of UAVs increases the study’s success. This study aims to determine the most suitable one among the innovative methods that constitute the image processing system for a UAV to be used for surveillance purposes.

Design/methodology/approach

Analytical hierarchy process has been used in the solution of the decision problem to be handled in three stages, namely, platform, architecture and method. The most suitable alternative and the effect weights of these criteria results were determined at each stage.

Findings

As a result of this study, Jetson TX2 was determined as the most suitable embedded platform, ResNet is the optimum architecture and Faster R-convolutional neural networks was the best method in the image processing layer for a system that will provide surveillance with image processing method using UAV.

Practical implications

In UAV designs, where multiple hardware and software choices and system combinations exist, multi-criteria decision-making (MCDM) approaches can be used as a system decision mechanism.

Originality/value

The novelty of this work comes from the application of MCDM methods that are used as a multi-layered decision mechanism in UAV design.

Details

Aircraft Engineering and Aerospace Technology, vol. 95 no. 3
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 14 March 2016

Guohong Zhang and Binjie Xin

This paper aims to overview the current status of development and application of digital image processing technology used for the yarn hairiness evaluation.

Abstract

Purpose

This paper aims to overview the current status of development and application of digital image processing technology used for the yarn hairiness evaluation.

Design/methodology/approach

Digital image processing technology is one of the new methods used for the yarn detection, which can be used for the digital characterization and objective evaluation of yarn appearance. The comparison between the traditional detection methods and this new developed method was made and analyzed.

Findings

Compared with the traditional methods, image-based methods have the advantages of being objective, fast and accurate. Therefore, it was proved that digital image processing techniques should be a new trend in terms of the yarn appearance evaluation.

Details

Research Journal of Textile and Apparel, vol. 20 no. 1
Type: Research Article
ISSN: 1560-6074

Keywords

Article
Publication date: 17 August 2012

Yanling Xu, Huanwei Yu, Jiyong Zhong, Tao Lin and Shanben Chen

The purpose of this paper is to analyze the technology of capturing and processing weld images in real‐time, which is very important to the seam tracking and the weld quality…

1092

Abstract

Purpose

The purpose of this paper is to analyze the technology of capturing and processing weld images in real‐time, which is very important to the seam tracking and the weld quality control during the robotic gas tungsten arc welding (GTAW) process.

Design/methodology/approach

By analyzing some main parameters on the effect of image capturing, a passive vision sensor for welding robot was designed in order to capture clear and steady welding images. Based on the analysis of the characteristic of the welding images, a new improved Canny algorithm was proposed to detect the edges of seam and pool, and extract the seam and pool characteristic parameters. Finally, the image processing precision was verified by the random welding experiments.

Findings

It was found that the seam and pool images can be clearly acquired by using the passive vision system, and the welding image characteristic parameters were accurately extracted through processing. The experiment results show that the precision range of the image processing can be controlled about within ±0.169 mm, which can completely meet the requirement of real‐time seam tracking for welding robot.

Research limitations/implications

This system will be applied to the industrial welding robot production during the GTAW process.

Originality/value

It is very important for the type of teaching‐playback robots with the passive vision that the real‐time images of seam and pool are acquired clearly and processed accurately during the robotic welding process, which helps determine follow‐up seam track and the control of welding quality.

Details

Industrial Robot: An International Journal, vol. 39 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 8 July 2010

Chris Town and Karl Harrison

Content‐based image retrieval (CBIR) technologies offer many advantages over purely text‐based image search. However, one of the drawbacks associated with CBIR is the increased…

Abstract

Purpose

Content‐based image retrieval (CBIR) technologies offer many advantages over purely text‐based image search. However, one of the drawbacks associated with CBIR is the increased computational cost arising from tasks such as image processing, feature extraction, image classification, and object detection and recognition. Consequently CBIR systems have suffered from a lack of scalability, which has greatly hampered their adoption for real‐world public and commercial image search. At the same time, paradigms for large‐scale heterogeneous distributed computing such as grid computing, cloud computing, and utility‐based computing are gaining traction as a way of providing more scalable and efficient solutions to large‐scale computing tasks.

Design/methodology/approach

This paper presents an approach in which a large distributed processing grid has been used to apply a range of CBIR methods to a substantial number of images. By massively distributing the required computational task across thousands of grid nodes, very high through‐put has been achieved at relatively low overheads.

Findings

This has allowed one to analyse and index about 25 million high resolution images thus far, while using just two servers for storage and job submission. The CBIR system was developed by Imense Ltd and is based on automated analysis and recognition of image content using a semantic ontology. It features a range of imageprocessing and analysis modules, including image segmentation, region classification, scene analysis, object detection, and face recognition methods.

Originality/value

In the case of content‐based image analysis, the primary performance criterion is the overall through‐put achieved by the system in terms of the number of images that can be processed over a given time frame, irrespective of the time taken to process any given image. As such, grid processing has great potential for massively parallel content‐based image retrieval and other tasks with similar performance requirements.

Details

Aslib Proceedings, vol. 62 no. 4/5
Type: Research Article
ISSN: 0001-253X

Keywords

Article
Publication date: 12 August 2021

Ali Sezer and Aytaç Altan

In the production processes of electronic devices, production activities are interrupted due to the problems caused by soldering defects during the assembly of surface-mounted…

1331

Abstract

Purpose

In the production processes of electronic devices, production activities are interrupted due to the problems caused by soldering defects during the assembly of surface-mounted elements on printed circuit boards (PCBs), and this leads to an increase in production costs. In solder paste applications, defects that may occur in electronic cards are usually noticed at the last stage of the production process. This situation reduces the efficiency of production and causes delays in the delivery schedule of critical systems. This study aims to overcome these problems, optimization based deep learning model has been proposed by using 2D signal processing methods.

Design/methodology/approach

An optimization-based deep learning model is proposed by using image-processing techniques to detect solder paste defects on PCBs with high performance at an early stage. Convolutional neural network, one of the deep learning methods, is trained using the data set obtained for this study, and pad regions on PCB are classified.

Findings

A total of six types of classes used in the study consist of uncorrectable soldering, missing soldering, excess soldering, short circuit, undefined object and correct soldering, which are frequently used in the literature. The validity of the model has been tested on the data set consisting of 648 test data.

Originality/value

The effect of image processing and optimization methods on model performance is examined. With the help of the proposed model, defective solder paste areas on PCBs are detected, and these regions are visualized by taking them into a frame.

Details

Soldering & Surface Mount Technology, vol. 33 no. 5
Type: Research Article
ISSN: 0954-0911

Keywords

Article
Publication date: 27 March 2009

Ntogas Nikolaos and Ventzas Dimitrios

The purpose of this paper is to introduce an innovative procedure for digital historical documents image binarization based on image pre‐processing and image condition…

Abstract

Purpose

The purpose of this paper is to introduce an innovative procedure for digital historical documents image binarization based on image pre‐processing and image condition classification. The estimated results for each class of images and each method have shown improved image quality for the six categories of document images described by their separate characteristics.

Design/methodology/approach

The applied technique consists of five stages, i.e. text image acquisition, image preparation, denoising, image type classification in six categories according to image condition, image thresholding and final refinement, a very effective approach to binarize document images. The results achieved by the authors' method require minimal pre‐processing steps for best quality of the image and increased text readability. This methodology performs better compared to current state‐of‐the‐art adaptive thresholding techniques.

Findings

An innovative procedure for digital historical documents image binarization based on image pre‐processing, image type classification in categories according to image condition and further enhancement. This methodology is robust and simple, with minimal pre‐processing steps for best quality of the image, increased text readability and it performs better compared to available thresholding techniques.

Research limitations/implications

The technique consists of limited but optimized pre‐processing sequential steps, and attention should be given in document image preparation and denoising, and on image condition classification for thresholding and refinement, since bad results in a single stage corrupt the final document image quality and text readability.

Originality/value

The paper contributes in digital image binarization of text images suggesting a procedure based on image preparation, image type classification and thresholding and image refinement with applicability on Byzantine historical documents.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 2 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 15 June 2015

Li Juan Yang, Pei Huang Lou and Xiao Ming Qian

The main purpose of this paper is to develop a method to recognize the initial welding position for large-diameter pipeline automatically, and introduce the image processing based…

Abstract

Purpose

The main purpose of this paper is to develop a method to recognize the initial welding position for large-diameter pipeline automatically, and introduce the image processing based on pulse-coupled neural network (PCNN) which is adopted by the proposed method.

Design/methodology/approach

In this paper, a passive vision sensor is designed to capture weld seam images in real time. The proposed method contains two steps. The first step is to detect the rough position of the weld seam, and the second step is to recognize one of the solder joints from the local image and extract its centroid, which is regarded as the initial welding position. In each step, image segmentation and removal of small false regions based on PCNN are adopted to obtain the object regions; then, the traditional image processing theory is used for the subsequent processing.

Findings

The experimental results show the feasibility and real time of the proposed method. Based on vision sensing technology and PCNN, it is able to achieve the autonomous recognition of initial welding position in large-diameter pipeline welding.

Practical implications

The proposed method can greatly shorten the time of positioning the initial welding position and satisfy the automatic welding for large-diameter pipeline.

Originality/value

In the proposed method, the image pre-processing is based on PCNN, which is more robust and flexible in the complex welding environment. After that, traditional image processing theory is adopted for the subsequent processing, of which the processing speed is faster.

Details

Industrial Robot: An International Journal, vol. 42 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

1 – 10 of over 107000