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Article
Publication date: 7 December 2021

Thorsten Stephan Beck

This paper provides an introduction to research in the field of image forensics and asks whether advances in the field of algorithm development and digital forensics will…

Abstract

Purpose

This paper provides an introduction to research in the field of image forensics and asks whether advances in the field of algorithm development and digital forensics will facilitate the examination of images in the scientific publication process in the near future.

Design/methodology/approach

This study looks at the status quo of image analysis in the peer review process and evaluates selected articles from the field of Digital Image and Signal Processing that have addressed the discovery of copy-move, cut-paste and erase-fill manipulations.

Findings

The article focuses on forensic research and shows that, despite numerous efforts, there is still no applicable tool for the automated detection of image manipulation. Nonetheless, the status quo for examining images in scientific publications remains visual inspection and will likely remain so for the foreseeable future. This study summarizes aspects that make automated detection of image manipulation difficult from a forensic research perspective.

Research limitations/implications

Results of this study underscore the need for a conceptual reconsideration of the problems involving image manipulation with a view toward the need for interdisciplinary collaboration in conjunction with library and information science (LIS) expertise on information integrity.

Practical implications

This study not only identifies a number of conceptual challenges but also suggests areas of action that the scientific community can address in the future.

Originality/value

Image manipulation is often discussed in isolation as a technical challenge. This study takes a more holistic view of the topic and demonstrates the necessity for a multidisciplinary approach.

Details

Journal of Documentation, vol. 78 no. 5
Type: Research Article
ISSN: 0022-0418

Keywords

Book part
Publication date: 8 July 2021

Ġorġ Mallia

This chapter seeks to present a limited overview of some aspects of manipulated and/or fake images that contribute to society ‘becoming post-truth’. It subclassifies…

Abstract

This chapter seeks to present a limited overview of some aspects of manipulated and/or fake images that contribute to society ‘becoming post-truth’. It subclassifies levels of manipulation and also presents the finding from a descriptive survey that gauges perceptions on awareness and recognisability of fake images. It also presents perceptions of effect on individuals of images modified for aesthetic reasons and carried by social media. The majority of respondents seemed affected by this, but with only a minority whose perception of self was affected. Another result of the survey is that there is a general mistrust of images not carried by gatekept sources.

Details

Media, Technology and Education in a Post-Truth Society
Type: Book
ISBN: 978-1-80043-907-8

Keywords

Article
Publication date: 17 June 2021

Ambica Ghai, Pradeep Kumar and Samrat Gupta

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be…

Abstract

Purpose

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

Design/methodology/approach

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

Findings

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

Research limitations/implications

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

Practical implications

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

Social implications

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

Originality/value

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

Details

Information Technology & People, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 27 August 2021

Xiaoyu Wang and Chenhong Ding

Country of origin (COO) effect refers to the influence of COO on consumers' perception and evaluation of a product. This research explores the impact of consumers' power…

Abstract

Purpose

Country of origin (COO) effect refers to the influence of COO on consumers' perception and evaluation of a product. This research explores the impact of consumers' power distance on COO effect.

Design/methodology/approach

We conducted two experiments to test the relevant hypotheses.

Findings

The results indicate that power distance has a polarizing influence on COO effect. That means, for products from countries with good images, the higher the consumers' power distance, the better their evaluation of the products; while for products from countries with poor images, the higher the power distance, the worse their evaluation of the products. The research also finds the moderating effect of consumers' competence–related country-related affect (CRA). When holding positive competence–related CRA, for products from countries with good images, the higher the consumers' power distance, the better their evaluation of the products; for products from countries with poor images, consumers' power distance has no effect. When having negative competence–related CRA, for products from countries with poor images, the higher the consumers' power distance, the worse their evaluation of the products; for products from countries with good images, power distance has no effect.

Originality/value

This study finds that depending on the perception of COO image, power distance not only improves the evaluation of products but also lows such evaluation, reflecting a two-way polarizing feature.

Details

Journal of Contemporary Marketing Science, vol. 4 no. 2
Type: Research Article
ISSN: 2516-7480

Keywords

Article
Publication date: 7 June 2021

Ying-Feng Kuo, Jian-Ren Hou and Yun-Hsi Hsieh

Netizens refer to citizens of the internet, and code-switching refers to the use of more than one language, style or form of expression to communicate. This study explores…

Abstract

Purpose

Netizens refer to citizens of the internet, and code-switching refers to the use of more than one language, style or form of expression to communicate. This study explores the advertising communication effectiveness of using netizen language code-switching in Facebook ads. Moreover, if a brand is with negative brand images, using positive brand images as a control group, this study investigates not only the advertising communication effectiveness of netizen language code-switching but also its effectiveness of remedying the negative brand images.

Design/methodology/approach

Online experiments were conducted, and data were analyzed using independent sample t-test, MANOVA and ANOVA.

Findings

The results indicate that netizen language code-switching can enhance advertising communication effectiveness in Facebook ads. Furthermore, under a negative brand image, netizen language code-switching has significant effects on improving Facebook advertising communication effectiveness.

Originality/value

This study takes netizens as the research subjects to explore the advertising communication effectiveness of netizen language code-switching in Facebook ads. This study provides further insight into the effect of netizens' culture on Facebook advertising and enriches the existing literature on social media advertising, as well as expanding the application of code-switching. The results of this study provide enterprises a new perspective on the copywriting content design of Facebook ads.

Details

Internet Research, vol. 31 no. 5
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 1 August 2005

Roslina Othman

This paper seeks to report on the study that proposed a model of image retrieval tasks for creative multimedia. The aim of this model was to understand the purpose of the…

1385

Abstract

Purpose

This paper seeks to report on the study that proposed a model of image retrieval tasks for creative multimedia. The aim of this model was to understand the purpose of the tasks, intended use of the images, mode of query submission, nature of the keywords given by the users, and relevance criteria.

Design/methodology/approach

A survey was done to compile a total of 35 image retrieval tasks from 35 academic staff members at Faculty of ICT, International Islamic University Malaysia, and Faculty of Creative Multimedia, Malaysia. A search using Google Image Search category was carried out to find images on the web that met the intended use of the academic staff members.

Findings

Findings revealed that images were mostly intended for analysis, decorations, design, illustrations, image processing, and inspiration. Users preferred linguistic query mode, and visual query mode if they had a sample of the image. Most users requested images with captions for making the relevance judgment. Technical attributes, topicality, and completeness were the most important relevance criteria. Users' keywords were of abstract and concrete elements, and were expressed in a visual way and as a subject. Images decided as relevant ranged from an object in the image to the whole image. This model reflected similar findings to other studies with some variations.

Practical implications

Results are useful for understanding the nature of image retrieval tasks for the area of creative multimedia.

Originality/value

This paper developed a model of image retrieval tasks in the area of creative multimedia, and offers a value in understanding the tasks that are intended to meet the demand of the Creative Multimedia Industry established in Malaysia.

Details

Performance Measurement and Metrics, vol. 6 no. 2
Type: Research Article
ISSN: 1467-8047

Keywords

Article
Publication date: 1 September 2004

Paul F. Whelan and Robert Sadleir

This paper details a free image analysis and software development environment for machine vision application development. The environment provides high‐level access to…

Abstract

This paper details a free image analysis and software development environment for machine vision application development. The environment provides high‐level access to over 300 image manipulation, processing and analysis algorithms through a well‐defined and easy to use graphical interface. Users can extend the core library using the developer's interface via a plug‐in which features automatic source code generation, compilation with full error feedback and dynamic algorithm updates. Also discusses key issues associated with the environment and outline the advantages in adopting such a system for machine vision application development.

Details

Sensor Review, vol. 24 no. 3
Type: Research Article
ISSN: 0260-2288

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…

2248

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: 23 September 2020

Deepak S. Kumar, Keyoor Purani and Shyam A. Viswanathan

This paper aims to introduce the concept of biomorphism (i.e. indirect experience of nature) in servicescape designs and validates its impact on consumer responses. Using…

2397

Abstract

Purpose

This paper aims to introduce the concept of biomorphism (i.e. indirect experience of nature) in servicescape designs and validates its impact on consumer responses. Using the stimulus-organism-response (S-O-R) framework, this study explores the relationship between biomorphic servicescape designs and the servicescape preference. Further, it explains how biomorphic designs can help users to get better connected with the servicescapes by introducing the mediating role of attention restoration and place identity (emotional and cognitive), as explained by attention restoration theory.

Design/methodology/approach

Two empirical studies were carried out to test the hypothesised relationships: an exploratory pre-experimental design with one-shot treatment using 200 images as stimuli and 3,680 responses; and a 3 × 2 factorial design with three-dimensional images with about 654 responses for three service contexts chosen a priori: fashion retail, restaurant and hospital lobby.

Findings

This study conceptualises the role of biomorphism – elements that mimic natural forms – in servicescape designs and establishes that, akin to natural elements, the indirect experience of nature in servicescapes also has a positive influence on attention restoration, perceived place identity and servicescape preference of the consumers. This implies that the effects similar to that of a biophilic servicescape can be achieved through servicescape elements that mimic natural forms.

Originality/value

Extending the idea of biophilia, this research adopts the concept of biomorphism from architecture and environmental psychology domains and introduces biomorphic servicescape designs, which could be more practical at times compared to biophilic servicescapes. It establishes the influences of biomorphic servicescape designs on consumer preferences. Grounded in the S-O-R model, it further explains this relationship through mediating effects of attention restoration and place identity. Being new to marketing and management domains, this research may trigger a series of research studies on biomorphic service environment designs, with desirable implications for services marketing and services operations functions.

Article
Publication date: 1 June 1990

There are a number of reasons why you might want to install equipment to capture and display images. It could be to reduce the long‐term costs of storing paper documents…

Abstract

There are a number of reasons why you might want to install equipment to capture and display images. It could be to reduce the long‐term costs of storing paper documents and to provide an efficient retrieval and dissemination mechanism. It might be to develop a desktop publishing system or create your own video‐based training tools.

Details

The Electronic Library, vol. 8 no. 6
Type: Research Article
ISSN: 0264-0473

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