Remote Network Monitoring Technology Based on Computer Technology

With the rapid development of Internet technology, using images to express the characteristics of things more direct, compared with text, audio, image expression content is more ambiguous, which makes the rapid increase of digital images on the Internet. Nowadays one of the hot directions of computer vision research is how to accurately and quickly retrieve the target image from a large amount of image data. This paper summarizes the development of image retrieval technology at home and abroad, and proposes an image search method based on color histogram and Chi-square distance. This paper discusses how to construct an image search system, which can search the image quickly, describe the color distribution of the photo with color histogram, divide the image into five regions, extract image features from the color histogram of each region, and then get the data set of multi-dimensional image features. Then the chi-square distance is used to calculate the similarity of color histogram, and the closest image is selected as the first similar image, which realizes the necessary logic of receiving query image and returning related results.

Multimodal Wireless Situational Awareness-Based Tourism Service Scene

Community platforms featuring user sharing and self-expression in social media generate big data on tourism resources, which, if fully utilized in a smart tourism system driven by high-tech and new technologies, will bring new life to the field of smart tourism research and will play an important role in the development of Internet+ tourism. However, tourism data in social media has the following characteristics: diversity, redundancy, heterogeneity, and intelligence. To address the characteristics of tourism data in social media, this thesis focuses on the following challenges: it is difficult to efficiently obtain tourism visualization information (text and images) in social media; it is difficult to effectively utilize tourism multimodal heterogeneous information; it is difficult to properly retrieve multimedia entity information of tourism attractions; and it is difficult to reasonably construct tourism personalized recommendation models. In this paper, an image search reordering method based on a hybrid feature graph model is proposed to realize the rapid acquisition of high-quality Internet images from the web using hybrid visual features and graph models, thus providing data security for the analysis of social media-based tourism images. To address the shortcomings of current search engines for image retrieval, visual information is used to bridge the problem of semantic gap between text-based search and images. To address the limitation of single visual features, we use latent semantic analysis to fuse multiple visual features to obtain hybrid features, which not only combine multiple single features but also preserve the potential relationship between these features. To address the shortcomings of the reordering methods based on classification and clustering, a reordering framework based on the graph model is used to reorder the images and finally complete the image search reordering based on the hybrid feature graph model. This method can obtain image information in social media with high efficiency and quality and then prepare for the subsequent work of tourism image analysis mining and personalized recommendation.

Trace the Untraceable: Online Image Search Tools for Researching Late Antique Art

In the context of digital humanities and access to cultural heritage online, this paper explores the discoverability of Late Antique material in some searchable museum collections and in some major archaeological and art historical image and object databases. It follows an exploratory approach by using simple keyword searches, such as ‘late antique’ or ‘byzantine’, and comparing the results with chronological searches when a date or period filter is available. Although Late Antique material often comprises a smaller number of objects compared to more popular periods like the Roman and the Renaissance, these are difficult to research due to inconsistent labelling practices and the frequent lack of a customizable date range filter. The ongoing debates on proper periodization and nomenclature also need to be taken into consideration.

Saudi women driving: images, stereotyping and digital media

This article examines the representations of Saudi women driving that circulated shortly after the lifting of the ban and considers the social, commercial and technological forces that helped to shape those representations . A corpus of images was collected from two international image banks – Getty and Shutterstock – as well as from a Google Image search. The images use Van Leeuwen’s (2008) visual representation framework in Discourse and Practice: New Tools for Critical Analysis, paying particular attention to the similarities and differences between the images available in the image banks and those that were made prominent in the Google search. In addition, semantic metadata accompanying these images were also analysed in order to understand the linguistic constraints that had been put on searches for these images and the ontologies of the issue that they promoted. Finally, a more detailed analysis was performed on images that had been appropriated into different contexts such as news stories and advertisements to investigate how these images were adapted to support different political, cultural and commercial agendas. Findings suggest that images of Saudi women that circulated online internationally shortly after the lifting of the ban were mostly generic and decontextualized, creating simplified and trivialized depictions of gender relations and social change in the Kingdom. The analysis shows how commercial concerns which influence both the creation of stock images and the way they are taken up by news organizations and advertisers can sometimes have the effect of erasing the complexity of political events and reinforcing the very stereotypes they seem to be challenging.