We propose an approach to index raster images of dictionary pages which in turn would require very little manual effort to enable direct access to the appropriate pages of the dictionary for lookup. Accessibility is further improved by feedback and crowdsourcing that enables highlighting of the specific location on the page where the lookup word is found, annotation, digitization, and fielded searching. This approach is equally applicable on simple scripts as well as complex writing systems. Using our proposed approach, we have built a Web application called "Dictionary Explorer" which supports word indexes in various languages and every language can have multiple dictionaries associated with it. Word lookup gives direct access to appropriate pages of all the dictionaries of that language simultaneously. The application has exploration features like searching, pagination, and navigating the word index through a tree-like interface. The application also supports feedback, annotation, and digitization features. Apart from the scanned images, "Dictionary Explorer" aggregates results from various sources and user contributions in Unicode. We have evaluated the time required for indexing dictionaries of different sizes and complexities in the Urdu language and examined various trade-offs in our implementation. Using our approach, a single person can make a dictionary of 1,000 pages searchable in less than an hour.
These three libraries are good sources of scanned images of dictionaries. Mirdeghan conducted a survey to compare the interfaces of these three libraries, which shows that the majority of participants preferred Open Library followed by Google Books @cite_3 . Our interface idea is inspired by the Open Library BookReader interface with extra features specific to dictionary exploration.
@cite_3
2118322263 2084989254 2163630478 2475804173
There are currently two dominant interface types for searching and browsing large image collections: keyword-based search, and searching by overall similarity to sample images. We present an alternative based on enabling users to navigate along conceptual dimensions that describe the images. The interface makes use of hierarchical faceted metadata and dynamically generated query previews. A usability study, in which 32 art history students explored a collection of 35,000 fine arts images, compares this approach to a standard image search interface. Despite the unfamiliarity and power of the interface (attributes that often lead to rejection of new search interfaces), the study results show that 90 of the participants preferred the metadata approach overall, 97 said that it helped them learn more about the collection, 75 found it more flexible, and 72 found it easier to use than a standard baseline system. These results indicate that a category-based approach is a successful way to provide access to image collections. This article proposes a process to retrieve the URL of a document for which metadata records exist in a digital library catalog but a pointer to the full text of the document is not available. The process uses results from queries submitted to Web search engines for finding the URL of the corresponding full text or any related material. We present a comprehensive study of this process in different situations by investigating different query strategies applied to three general purpose search engines (Google, Yahoo!, MSN) and two specialized ones (Scholar and CiteSeer), considering five user scenarios. Specifically, we have conducted experiments with metadata records taken from the Brazilian Digital Library of Computing (BDBComp) and The DBLP Computer Science Bibliography (DBLP). We found that Scholar was the most effective search engine for this task in all considered scenarios and that simple strategies for combining and re-ranking results from Scholar and Google significantly improve the retrieval quality. Moreover, we study the influence of the number of query results on the effectiveness of finding missing information as well as the coverage of the proposed scenarios. While many digital libraries focus on supporting defined tasks that require targeted searching, there is potential for enabling serendipitous discovery that can serve multiple purposes from aiding with the targeted search to suggesting new approaches, methods and ideas. In this research we embedded a tool in a novel interface to suggest other pages to examine in order to assess how that tool might be used while doing focused searching. While only 40 of the participants used the tool, all assessed its usefulness or perceived usefulness. Most participants used it as a source of new terms and concepts to support their current tasks; a few noted the novelty and perceived its potential value in serving as a stimulant. The BGSLibrary has been designed to provides an easy-to-use C++ framework and tools to perform background subtraction. First released in March 2012, currently the library offers 32 background subtraction algorithms. The source code is available under GNU GPL v3 license and the library is free for non-commercial use, open source and platform independent. Note that the license of the algorithms included in BGSLibrary not necessarily have the same license of the library. Some authors do not allow that their algorithms will be used for a commercial purpose, first is needed to contact them to ask permission. However, by default, we decided to adopt the GPL-v3 license. The BGSLibrary also provides one Java based GUI (Graphical User Interface) allowing the users to configure the input video-source, region of interest, and the parameters of each BS algorithm. A MFC-based GUI is also provided for a quick access in Windows computers. But, a QT-based GUI is coming for a platform independent usage. To build run the BGSLibrary, it is necessary to have the OpenCV library installed previously. Everyone is invited to collaborate with the BGSLibrary. In this chapter some efforts has been made for how to make and add your contributions in the library. Feel free to contact us to suggest and share your ideas. We are open to innovations!