Heritage Image Research Articles

Heritage image annotation via collective knowledge

The automatic image annotation can provide semantic illustrations to understand image contents, and builds a foundation to develop algorithms that can search images within a large database. However, most current methods focus on solving the annotation problem by modeling the image visual content and tag semantic information, which overlooks the additional information, such as scene descriptions and locations. Moreover, the majority of current annotation datasets are visually consistent and only annotated by common visual objects and attributes, which makes the classic methods vulnerable to handle the more diverse image annotation. To address above issues, we propose to annotate images via collective knowledge, that is, we uncover relationships between the image and its neighbors by measuring similarities among metadata and conduct the metric learning to obtain the representations of image contents, we also generate semantic representations for images given collective semantic information from their neighbors. Two representations from different paradigms are embedded together to train an annotation model. We ground our model on the heritage image collection we collected from the library online open data. Annotations on the heritage image collection are not limited to common visual objects, and are highly relevant to historical events, and the diversity of the heritage image content is much larger than the current datasets, which makes it more suitable for this task. Comprehensive experimental results on the benchmark dataset indicate that the proposed model achieves the best performance compared to baselines and state-of-the-art methods.

The Second Skin of the Heritage Cities, Old Mosul Second Skin

The images of the heritage cities are the key of the conservation process that deals with the visible and invisible factors. The psychological effects of the image on the recipients’ cognitive process can create an aesthetic value of the city. There are two types of skins , which are visible and invisible. The invisible skin is; the skin generated between the recipient’s body and the skin of the place. The matching between these skins can create the second skin, which positively or negatively affects the image of the heritage cities. The study is to identify the second skin of the old Mosul city as in-depth documentation of the heritage elements that can create the matching of the two skins. The research question of the study is “What are the elements of the psychical second skin in the heritage city of Mosul”. Therefore, the study used a mixed methodology (Qualitative and Quantitative) to reach the aim of the study. Survey technique used to find the answer from the users of the place, also interview with architectural and heritage experts. The primary results show that the second skin of the city depends on the intangible element more than tangible. Therefore, urban elements have a giant impact on the image of the place. The conservation processes should focus on the elements that can sustain the skin of the city as a heritage image and inherited a tangible and intangible culture.

Heritage Image and Attitudes toward a Heritage Site: Do They Really Mediate the Relationship between User-Generated Content and Travel Intentions toward a Heritage Site?

Traveling to heritage sites represents a growing sector with great potential in the context of heritage tourism, which is a relevant topic but has received little scholarly attention. The present study tries to bridge this gap by investigating the mediating role of heritage image and attitudes toward a heritage site in the relationship between user-generated content (UGC) and travel intention toward a heritage site. In particular, we applied partial least squares structural equation modeling (PLS-SEM), which is a relatively popular new method, instead of the traditionally used covariance-based structural equation modeling (CB-SEM) method. The rise in popularity of PLS-SEM has been particularly noticeable since 2013, but in the area of heritage tourism, research is still in an early stage of development because the heritage discipline has hardly exploited the benefits of this approach. We proposed a multimediation model for heritage tourism to address this relatively new research avenue. It was discovered that exogenous variables directly and indirectly influenced travel intentions toward a heritage site through their mediators (i.e., heritage image and attitudes toward a heritage site). The findings provide an appropriate empirical and theoretical conclusion as well as valuable insights for heritage management organizations (HMOs) into the performance of heritage tourism, both for local professionals and the host communities that assist in increasing the development of heritage tourism.

Adaptive features selection for expert datasets: A cultural heritage application

Image Retrieval is still a very active field of image processing as the number of available image datasets continuously increases. One of the principal objectives of Content-Based Image Retrieval (CBIR) is to return to user the most similar images to a given query with respect to their visual content. Our work fits in a very specific application context: indexing small expert image dataset, e.g. cultural heritage images, with no prior knowledge on the images. Because of the image complexity, one of our contributions is the choice of effective descriptors from literature placed in direct competition. Two strategies are used to combine features: a psycho-visual one and a statistical one. In this context, we propose an automatic and adaptive framework based on the well-known bags of visual words and phrases models that select relevant visual descriptors for each keypoint to construct a more discriminative image representation. Experiment results show the adaptiveness and the performance of our framework on “generic” benchmark datasets and on two cultural heritage datasets.

Figure spotting in Indian heritage image

Abstract Figure spotting is one of the important applications in the field of content-based image retrieval. With the recent advances in 3D shape analysis, Wave Kernel Signature (WKS), a kernel-based feature descriptor under the foundation of quantum mechanics performs well than the other kernel based feature descriptors. In this paper, we adopt the WKS as a 2D local patch descriptor for figure spotting. An effective search technique is developed to spot the regions of interest within an image for a given query image. We also use the classical feature descriptors such as scale-invariant feature transform (SIFT), speeded up robust features (SURF), and the histogram of oriented gradients (HOG) for figure spotting and compare their performances. The proposed technique is tested on a dataset which contains 594 images collected from two heritage temples. The performance of the proposed technique is measured using standard evaluation metrics and shows promising results of the proposed method.

Unforgettable brands: image heritage and consumer engagement in online communities

Purpose of the paper: The paper identifies a link between the consumers’ image heritage and consumer engagement towards brand and community. This objective is focused on a virtual brand community, in the context of non-grocery retailing. Methodology: A simple random sample was extracted from the Italian online community of Leroy Merlin. Data was collected through 100 Skype interviews. The collected data has been submitted to bivariate analysis. Findings: There is a noticeable dependence between image heritage and consumer brand engagement, as well as between image heritage and consumer community engagement. Research limits: Chi-square value, that verifies the relationship between constructs, depends on the sample size. Perspectives of other relevant stakeholders are not adopted. Online brand communities, created by firms, are the only ones to be investigated. Generalizing findings is another limit. Practical implications: It is not possible to engage the consumer if brand managers ignore or underestimate a planned management of image heritage. To engage the consumer means to discover, explore, enhance, and preserve the heritage image. Originality of the paper: This paper introduces the Consumer Image Heritage Engagement (CIHE), that is a synthesis of the starting constructs. An integrated framework is proposed in order to effectively and efficiently manage the CIHE.

Classification of Architectural Heritage Images Using Deep Learning Techniques

The classification of the images taken during the measurement of an architectural asset is an essential task within the digital documentation of cultural heritage. A large number of images are usually handled, so their classification is a tedious task (and therefore prone to errors) and habitually consumes a lot of time. The availability of automatic techniques to facilitate these sorting tasks would improve an important part of the digital documentation process. In addition, a correct classification of the available images allows better management and more efficient searches through specific terms, thus helping in the tasks of studying and interpreting the heritage asset in question. The main objective of this article is the application of techniques based on deep learning for the classification of images of architectural heritage, specifically through the use of convolutional neural networks. For this, the utility of training these networks from scratch or only fine tuning pre-trained networks is evaluated. All this has been applied to classifying elements of interest in images of buildings with architectural heritage value. As no datasets of this type, suitable for network training, have been located, a new dataset has been created and made available to the public. Promising results have been obtained in terms of accuracy and it is considered that the application of these techniques can contribute significantly to the digital documentation of architectural heritage.

National Identity in Mahmoud Darwish’s Poetry

This paper is intended to examine the concept of national identity and how it is quested and portrayed in Mahmoud Darwish’s poetry. The paper explores Darwish’s quest for identity through different phases: language, homeland, roots and ancerstors, belonging, nature, culture, traditions, and exile. Palestine for Darwish is not only an origin or homeland, but it is an identity. Darwish adds some themes connected with the concept of homeland illustrated by references or images of mother, geography, history, farming, and folkloric heritage. Besides, identity for Darwish is three- dimensional: Palestinian, national, and human.

Managing the future of the past: images of Exmoor landscape heritage

Tarr Steps is a footbridge across a river but it also bridges two temporal landscapes: the present and the ‘deep past’. Although the origins of the site are uncertain, the bridge is often represented as objectively authentic and ‘ancient’. The historicity of this claim is challenged by secondary production of the site. We unpack the discursive construction of the bridge and argue that Tarr Steps’ connection to the deep past is a cultural imaginary based on a selective interpretation of its morphology. This imaginary connection authenticates representation of the site as resembling the origin of a sequence of cultural evolution in Britain. We explore implications of this in relation to three metaphors of landscape used in the cultural heritage management tool called Historic Landscape Characterisation. In so doing, we raise questions about the future of the past, specifically in terms of the conceptualisation of temporality, authenticity and the politics of representation.

Efficient cultural heritage image restoration with nonuniform illumination enhancement

Cultural heritage digitization has been of research interest for several decades. For such, the quality of the stored images should be pleasant to see. However, as images captured by digital devices may include undesirable effects, conducting an enhancement on the image is essential. In this context, we present a framework for the purpose of cultural heritage image illumination enhancement. First, a mapping curve based on saturation feedback is created to adjust the contrast. Then illumination is enhanced by applying a modified homomorphic filter in the frequency domain. The technique employs an optimization search process based on the efficient golden section search algorithm to compute the optimal parameters to produce the enhanced image. Finally, a color restoration function is applied to overcome the problem of color violation. The resulted image represents a trade-off among local contrast improvement, detail enhancement, and preserving the naturalness of the image. Experiments are conducted on a collected dataset of cultural heritage images and compared to some of the state-of-the-art image enhancement methods using a set of quantitative assessments criteria. Results have shown that our proposed approach is able to accomplish a wide set of the performance goals.

The effects of heritage image on destination branding: an Iranian perspective

ABSTRACTAs brands are extremely influential in marketing, destinations should work to develop strong and recognizable brands for tourism to succeed in differentiating their competitive advantages over other destinations. The main purpose of this study is to identify the constituent elements of the overall image of the brand of Iran’s main heritage destinations by utilizing heritage, general, and unique images, and it proposes a model for branding Iran’s heritage destinations. The study population included 750 tourists and was conducted from August to the end of September 2013 in three Iranian historic cities. Results indicate that the heritage image and the unique image have a relationship with the general image of the destination, and that general image itself has a relationship with overall destination brand. The results also revealed that the overall destination image and brand are linked to tourists’ perceptions of the quality of the destination, and the quality itself has a relationship with tourists’ loyalty to the destination.

ASTROINFORMATICS AS A NEW RESEARCH FIELD: UKRVO AND VIRGO RESOURCES

ABSTRACT. The data-oriented astronomy has allowed classifying the Astroinformatics as a new academic research field, which covers various multi-disciplinary applications of the e-Astronomy. Among them are the data modeling, data mining, metadata standards development, data access, digital astronomical databases, image archives and visualization, machine learning, statistics and other computational methods and software for work with astronomical survey and catalogues with their teta- topeta-scale astroinformation resource. In this review we describe briefly the astroinformatics applications and software/services performed for different astronomical tasks in frame of the VIrtual Roentgen and Gamma Observatory (VIRGO) and Ukrainian VirtualObservatory (UkrVO). Among them there are projects based on the archival space-born data of X-ray and gamma space observatories and on the Joint Digitized Archive (JDA) database of astroplate network collections. The UkrVO JDA DR1 deals with the star catalogues (FON, Polar zone, open clusters, GRB star fields) as well as the UkrVO JDA DR2 deals with the Solar System bodies (giant and small planets, satellites, astronomical heritage images).

Data merging for the cultural heritage imaging based on Chebfun approach

Cultural heritage imaging has specific needs with regards to the analysis of images that require the manipulation of a single digital object that combines the images obtained from different instruments probing different scales at different wavelengths, with the further possibility of selecting two or three dimensional representations. We propose a unified imaging data processing approach based on the Chebyshev Technology using the open source software Chebfun which, by mapping data processing to simple polynomial transformations, brought considerable improvements over already existing procedures. Within that same data processing framework we may further investigate how to merge images originating from different acquisition devices since all images are expressed in the same basis (an approximate Chebfun polynomial basis ) before being merged. In the end, we hope to map all imaging data processing to simple polynomial operations. Our massive data-sets required parallelizing some Chebfun functions on GPUs, allowing about 100 times faster polynomial evaluation and up to 12 times faster on CPUs when parallelizing the whole algorithm.

Theming Asia: culture, nature and heritage in a transforming environment

ABSTRACTThis paper introduces a special issue on Theme Parks in Asia with reflections on how the various theoretical ideas on theming and theme parks that are found in the social science literature can help us to understand the proliferation of theming and theme parks in contemporary Asia. How does theming create a specific spatial and social form that has meaning in a transforming Asia? We trace here the rising importance of theming in places of consumption, education, entertainment and everyday life and argue that further attention is needed to understand the transformation of ideas of culture, nature and heritage within the context of theme park development in Asia. We look at arguments that suggest that theming is part of human cognitive processes, that it creates a frame that gives the content a particular order and meaning; we also consider theming within the context of theories of Disneyization and the ‘experience economy’ in leisure and tourism to explore how ‘new’ experience-based consumerism, and the designing of coherent ‘imagineered’ spaces, plays a role in ordering our social worlds. We also examine how debates over the authenticity or superficiality of theme parks, and more generally in cultural display and preservation, can take on new twists in Asia. We do this by drawing on a review of postmodernist perspectives on themed parks to show how theme parks in Asia can be better understood through nuanced inquiries into the ways cultural, natural and heritage images and icons are cited, referenced and projected, departing from a simple ‘copy’ versus ‘original’ dichotomy. Finally, we position and introduce the papers included in this special issue and suggest further possible research into such a fertile research field.

Comparative postcolonial ruralities and English heritage: Julian Barnes’s England, England and Kiran Desai’s The Inheritance of Loss

This article argues for the vastly different ways in which English heritage is celebrated as a legacy of the British Empire in rural spaces located both in England and in India. Comparing Julian Barnes’s satirical novel England, England (1998) with Kiran Desai’s The Inheritance of Loss (2006) affords disparate images of English heritage in postimperial Britain and in postcolonial India. Barnes parodies efforts by the English heritage industry, in an age of decline, to revivify English nationalism and to recollect erstwhile imperial glory. In a globalized world, he underscores the desire for nostalgia preoccupied with a mythic English agrarian past, its historical icons, and its social order as anachronistic instead of inspirational. At best, it appears historically ignorant; at worst, he suggests, it serves as a perversion of reality. For Barnes, the English heritage industry is self-indulgent and largely motivated by profit. In contrast, Desai’s novel represents the damage caused by a class structure forged from India’s colonial inheritance and a persistent privileging of English culture and heritage. Desai suggests economic power and social prestige, even in an obscure hill village in India, are articulated through material displays and personal knowledge of English heritage, reflecting the different classes’ uneven access to capital and knowledge. Her novel simultaneously depicts those at the bottom end of India’s class hierarchy who are compelled to acts of desperation in pursuit of better lives.

Life-cycle tradeoffs of plug-ins

Electric Vehicles![Figure][1] Roger Wallace in his electric car, 1899. PHOTO: © HERITAGE IMAGE PARTNERSHIP LTD / ALAMY STOCK PHOTO Shifting to electric passenger vehicles ideally will reduce the carbon footprint of the transportation sector. Two recent studies, however, show that the greenhouse gas emissions produced over the life cycle of electric vehicles, from production through use, may not always be less than those of gasoline-burning vehicles. Ellingsen et al. reveal that vehicle and battery size prohibit some larger electric vehicles from ever overcoming the high greenhouse gas emissions generated during production. Yuksel et al. show that regional factors in the United States such as electrical grid mix, temperature, and driving conditions strongly limit the potential of plug-in electric vehicles to out-perform high-efficiency gas vehicles. Blanket policies directed at the adoption of electric vehicles therefore could potentially fail to reduce the transportation sector's large carbon footprint. Environ. Res. Lett. 11, 054010, 044007 (2016). [1]: pending:yes

Finding cultural heritage images through a Dual-Perspective Navigation Framework

With the increasing volume of digital images, improving techniques for image findability is receiving heightened attention. The cultural heritage sector, with its vast resource of images, has realized the value of social tags and started using tags in parallel with controlled vocabularies to increase the odds of users finding images of interest. The research presented in this paper develops the Dual-Perspective Navigation Framework (DPNF), which integrates controlled vocabularies and social tags to represent the aboutness of an item more comprehensively, in order that the information scent can be maximized to facilitate resource findability.DPNF utilizes the mechanisms of faceted browsing and tag-based navigation to offer a seamless interaction between experts’ subject headings and public tags during image search. In a controlled user study, participants effectively completed more exploratory tasks with the DPNF interface than with the tag-only interface. DPNF is more efficient than both single descriptor interfaces (subject heading-only and tag-only interfaces). Participants spent significantly less time, fewer interface interactions, and less back tracking to complete an exploratory task without an extra workload. In addition, participants were more satisfied with the DPNF interface than with the others. The findings of this study can assist interface designers struggling with what information is most helpful to users and facilitate searching tasks. It also maximizes end users’ chances of finding target images by engaging image information from two sources: the professionals’ description of items in a collection and the crowd's assignment of social tags.

Estimation and Correction of Geometric Distortion in Pushbroom Hyperspectral System for Imaging Art Paintings

Spectral imaging has been proved as a promising technology to perform scientific documentation and analysis of cultural heritage objects. Imaging systems used for this purpose varies in different forms and complexity. Most of the spectral devices are designed not specifically for cultural heritage imaging, but for other application domains like remote sensing, satellite imaging etc. While these imaging systems used for cultural heritage scanning, the same processing workflow may not be adequate to meet the required image quality. In this paper, we investigate one of the several quality parameters, geometrical distortions in a spectral image caused by the translation stage of the camera. For this study, we used a hyperspectral image dataset derived from a pushbroom hyperspectral imaging system attached in a rotational translator. Using geometrical model, we have estimated the distortion, which is function of the scanning angle and distance. Image correction has been proposed and tested over a number of images acquired at the laboratory and in a museum environment.

Of Plaster Casts and Monks: Images of Cultural Heritage in Risorgimento Italy

Author(s): Napoli, J. Nicholas | Abstract: In a new nation formed from regions of differing political traditions and histories, no single work of art or building could emerge as an emblematic image of Italian culture. Instead, this essay argues that two classes of images – one an object type, the other the representation of a social class -- grew to epitomize the cultural identity crisis of the newly founded state. Both types of images, furthermore, were closely connected to the activities of the national superintendency. The first were products of the archaeological innovation of Giuseppe Fiorelli when he the director of the national museum in Naples in 1863: they were the plaster casts of the ancient Pompeiians who perished in the eruption of Vesuvius. The second were monks: members of the ancien regime’s privileged first estate and former residents of the ecclesiastic estates that became state property – some as national monuments – with the suppression of religious corporations in 1866.

The use of embedded metadata in heritage image workflows

With increasing scrutiny of museum and gallery public access and dissemination policies, heritage organisations are investing heavily in the online user experience. This includes allowing users to browse and search for images and other media of objects and artefacts held by the organisation. While public interface websites are attracting a lot of attention, their creators often forget that the media on them — generally images at present — can be viewed and used in environments other than the originating website. Heritage organisations encourage the public to download images and use them for private non-commercial purposes. This is where the use of embedded data becomes important. This paper details some of the ways embedded data may be used in practice, both in internal workflows and for images on publicly accessible websites.