Living Memory Annotation Tool – Image Annotations for Digital Libraries

Jochum, Wolfgang; Kaiser, Max; Schellner, Karin; Wirl, Franz

doi:10.1007/978-3-540-74851-9_66

Cited by 2 publications

(2 citation statements)

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“…Many digital libraries have annotation capabilities, usually focusing on annotations of complete documents. There has been work done to provide annotation support for image digital libraries such as [15], [16]. Also, there are several photo annotation systems, including online tools such as Flickr 6 and Fototagger 7 .…”

Section: Related Workmentioning

confidence: 99%

Superimposed Image Description and Retrieval for Fish Species Identification

Murthy

Fox

Chen

et al. 2009

Research and Advanced Technology for Digital Libraries

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Fish species identification is critical to the study of fish ecology and management of fisheries. Traditionally, dichotomous keys are used for fish identification. The keys consist of questions about the observed specimen. Answers to these questions lead to more questions till the reader identifies the specimen. However, such keys are incapable of adapting or changing to meet different fish identification approaches, and often do not focus upon distinguishing characteristics favored by many field ecologists and more user-friendly field guides. This makes learning to identify fish difficult for Ichthyology students. Students usually supplement the use of the key with other methods such as making personal notes, drawings, annotated fish images, and more recently, fish information websites, such as Fishbase. Although these approaches provide useful additional content, it is dispersed across heterogeneous sources and can be tedious to access. Also, most of the existing electronic tools have limited support to manage user created content, especially that related to parts of images such as markings on drawings and images and associated notes. We present SuperIDR, a superimposed image description and retrieval tool, developed to address some of these issues. It allows users to associate parts of images with text annotations. Later, they can retrieve images, parts of images, annotations, and image descriptions through text-and content-based image retrieval. We evaluated SuperIDR in an undergraduate Ichthyology class as an aid to fish species identification and found that the use of SuperIDR yielded a higher likelihood of success in species identification than using traditional methods, including the dichotomous key, fish web sites, notes, etc.

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Section: Related Workmentioning

confidence: 99%

Superimposed Image Description and Retrieval for Fish Species Identification

Murthy

Fox

Chen

et al. 2009

Research and Advanced Technology for Digital Libraries

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“…There are several applications which support services based on image content, allowing integration in distinct domains (Murthy et al, 2010;Achananuparp et al, 2007). And along with these applications, images can also be explored to integrate annotation support for image digital libraries such as (Jochum et al, 2007). In particular, consider for the following examples a recently developed component-based CBIR infrastructure aiming to process and encapsulate images and related data (Kozievitch et al, 2012;Kozievitch et al, 2011b), presented in Figure 3.…”

Section: Images and Applicationsmentioning

confidence: 99%

Exploring Data Fusion under the Image Retrieval Domain

Kozievitch

Hara

Nande

et al. 2014

Proceedings of the 16th International Conference on Enterprise Information Systems

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Advanced services in data compression, data storage, and data transmission have been developed and are widely used to address the required capabilities of an assortment of systems across diverse application domains. In order to reuse, integrate, unify, manage, and support heterogeneous resources, a number of works and concepts have emerged with the aim of facilitating aggregation of content and helping system developers. In particular, images, along with existing Content-Based Image Retrieval services, have the potential to play a key role in information systems, due to the large availability of images and the need to integrate them with existing collections, metadata, and available image manipulation softwares and applications. In this work, we explore a data fusion approach for solving data value conflicts in the context of image retrieval domain. In particular, we target the process of solving value conflicts resulted from different features integrating the data resulted from the Content-Based Image Retrieval process, along with the image metadata, provided from a number of sources and applications. Our approach reduces the need of human intervention for keeping a clean and integrated view of an image repository when new data sources are added to an image management system.

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Living Memory Annotation Tool – Image Annotations for Digital Libraries

Cited by 2 publications

References 0 publications

Superimposed Image Description and Retrieval for Fish Species Identification

Superimposed Image Description and Retrieval for Fish Species Identification

Exploring Data Fusion under the Image Retrieval Domain

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