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Image Search
An image retrieval system is a computer system used for browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval utilize some method of adding metadata such as captioning, keywords, title or descriptions to the images so that retrieval can be performed over the annotation words. Manual image annotation is time-consuming, laborious and expensive; to address this, there has been a large amount of research done on automatic image annotation. Additionally, the increase in social web applications and the semantic web have inspired the development of several web-based image annotation tools. The first microcomputer-based image database retrieval system was developed at MIT, in the 1990s, by Banireddy Prasaad, Amar Gupta, Hoo-min Toong, and Stuart Madnick. A 2008 survey article documented progresses after 2007. All image retrieval systems as of 2021 were designed for 2D images, not 3D ones. Search met ...
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List Of CBIR Engines
This is a list of publicly available Content-based image retrieval Content-based image retrieval, also known as query by image content ( QBIC) and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching ... (CBIR) engines. These image search engines look at the content (pixels) of images in order to return results that match a particular query. Commercial CBIR search engines CBIR research projects/demos/open source projects {, class="wikitable sortable" , - ! Name ! Description ! External Image Query ! Metadata Query ! Index Size (Estimate, Millions of Images) ! Organization Type ! License (Open/Closed) , - akiwi, akiwi is a semi-automatic image keywording tool using CBIR techniques. It was developed by HTW Berlin / pixolution GmbH , Yes , Yes , 15M , University , Closed , - ALIPR, Developed by Penn State University researchers , Yes , Yes , , Universit ...
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Database
In computing, a database is an organized collection of data stored and accessed electronically. Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases spans formal techniques and practical considerations, including data modeling, efficient data representation and storage, query languages, security and privacy of sensitive data, and distributed computing issues, including supporting concurrent access and fault tolerance. A database management system (DBMS) is the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS software additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a database system. Often the term "database" is also used loosely to refer to any of the DBMS, the database system or an app ...
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Automatic Image Annotation
Automatic image annotation (also known as automatic image tagging or linguistic indexing) is the process by which a computer system automatically assigns metadata in the form of captioning or keywords to a digital image. This application of computer vision techniques is used in image retrieval systems to organize and locate images of interest from a database. This method can be regarded as a type of multi-class image classification with a very large number of classes - as large as the vocabulary size. Typically, image analysis in the form of extracted feature vectors and the training annotation words are used by machine learning techniques to attempt to automatically apply annotations to new images. The first methods learned the correlations between image features and training annotations, then techniques were developed using machine translation Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-a ...
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Learning To Rank
Learning to rank. Slides from Tie-Yan Liu's talk at WWW 2009 conference aravailable online or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. Training data consists of lists of items with some partial order specified between items in each list. This order is typically induced by giving a numerical or ordinal score or a binary judgment (e.g. "relevant" or "not relevant") for each item. The goal of constructing the ranking model is to rank new, unseen lists in a similar way to rankings in the training data. Applications In information retrieval Ranking is a central part of many information retrieval problems, such as document retrieval, collaborative filtering, sentiment analysis, and online advertising. A possible architecture of a machine-learned search engine is shown in the accompanying figure. Training data c ...
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VisualRank
VisualRank is a system for finding and ranking images by analysing and comparing their content, rather than searching image names, Web links or other text. Google scientists made their VisualRank work public in a paper describing applying PageRank to Google image search at the International World Wide Web Conference in Beijing in 2008. . Methods Both computer vision techniques and locality-sensitive hashing (LSH) are used in the VisualRank algorithm. Consider an image search initiated by a text query. An existing search technique based on image metadata and surrounding text is used to retrieve the initial result candidates (PageRank), which along with other images in the index are clustered in a graph according to their similarity (which is precomputed). Centrality is then measured on the clustering, which will return the most canonical image(s) with respect to the query. The idea here is that agreement between users of the web about the image and its related concepts will ...
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Multimedia Information Retrieval
Multimedia information retrieval (MMIR or MIR) is a research discipline of computer science that aims at extracting semantic information from multimedia data sources.H Eidenberger. ''Fundamental Media Understanding'', atpress, 2011, p. 1. Data sources include directly perceivable media such as audio, image and video, indirectly perceivable sources such as text, semantic descriptions, biosignals as well as not perceivable sources such as bioinformation, stock prices, etc. The methodology of MMIR can be organized in three groups: # Methods for the summarization of media content ( feature extraction). The result of feature extraction is a description. # Methods for the filtering of media descriptions (for example, elimination of redundancy) # Methods for the categorization of media descriptions into classes. Feature extraction methods Feature extraction is motivated by the sheer size of multimedia objects as well as their redundancy and, possibly, noisiness. Generally, two possibl ...
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Information Retrieval
Information retrieval (IR) in computing and information science is the process of obtaining information system resources that are relevant to an information need from a collection of those resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds. Automated information retrieval systems are used to reduce what has been called information overload. An IR system is a software system that provides access to books, journals and other documents; stores and manages those documents. Web search engines are the most visible IR applications. Overview An information retrieval process begins when a user or searcher enters a query into the system. Queries are formal statements of information needs, for example search strings in web search engines. In ...
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Image Processing
An image is a visual representation of something. It can be two-dimensional, three-dimensional, or somehow otherwise feed into the visual system to convey information. An image can be an artifact, such as a photograph or other two-dimensional picture, that resembles a subject. In the context of signal processing, an image is a distributed amplitude of color(s). In optics, the term “image” may refer specifically to a 2D image. An image does not have to use the entire visual system to be a visual representation. A popular example of this is of a greyscale image, which uses the visual system's sensitivity to brightness across all wavelengths, without taking into account different colors. A black and white visual representation of something is still an image, even though it does not make full use of the visual system's capabilities. Images are typically still, but in some cases can be moving or animated. Characteristics Images may be two or three-dimensional, such as a ...
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Image Organizer
An image organizer or image management application is application software focused on organising digital images. Image organizers represent one kind of desktop organizer software applications. Image organizer software is primarily focused on improving the user's workflow by facilitating the handling of large numbers of images. In contrast to an image viewer, an image organizer has at least the additional ability to edit the image tags and often also an easy way to upload files to on-line hosting pages. Enterprises may use Digital Asset Management (DAM) solutions to manage larger and broader amounts of digital media. Some programs that come with desktop environments such as gThumb (GNOME) and digiKam (KDE) were originally programmed to be simple image viewers, and have since gained features to be used as image organizer as well. Common image organizers features * Multiple thumbnail previews are viewable on a single screen and printable on a single page. (Contact Sheet) * Ima ...
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Digital Image Editing
Image editing encompasses the processes of altering images, whether they are digital photographs, traditional photo-chemical photographs, or illustrations. Traditional analog image editing is known as photo retouching, using tools such as an airbrush to modify photographs or editing illustrations with any traditional art medium. Graphic software programs, which can be broadly grouped into vector graphics editors, raster graphics editors, and 3D modelers, are the primary tools with which a user may manipulate, enhance, and transform images. Many image editing programs are also used to render or create computer art from scratch. The term “image editing” usually refers only to the editing of 2D images, not 3D ones. Basics of image editing Raster images are stored in a computer in the form of a grid of picture elements, or pixels. These pixels contain the image's color and brightness information. Image editors can change the pixels to enhance the image in many ways. The ...
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Digital Asset Management
Digital asset management (DAM) and the implementation of its use as a computer application is required in the collection of digital assets to ensure that the owner, and possibly their delegates, can perform operations on the data files. Terminology The term ''media asset management'' (MAM) may be used in reference to Digital Asset Management when applied to the sub-set of digital objects commonly considered "media", namely audio recordings, photos, and videos. Any editing process that involves media, especially video, can make use of a MAM to access media components to be edited together, or to be combined with a live feed, in a fluent manner. A MAM typically offers at least one searchable index of the images, audio, and videos it contains constructed from metadata harvested from the images using pattern recognition, or input manually. Management Creation Applications implement digital asset management by importing it from the analog and/or digital domains (by encoding, ...
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Concept-based Image Indexing
Concept-based image indexing, also variably named as "description-based" or "text-based" image indexing/retrieval, refers to retrieval from text-based indexing of images that may employ keywords, subject headings, captions, or natural language text (Chen & Rasmussen, 1999). It is opposed to Content-based image retrieval. Indexing is a technique used in CBIR. Chu (2001) confirms that there exist two distinctive research groups employing the content-based and description-based approaches, respectively. However, research in the content-based domain is currently dominating in the field, while the other approach has less visibility. See also *Document classification *Subject (documents) In library and information science documents (such as books, articles and pictures) are classified and searched by subject – as well as by other attributes such as author, genre and document type. This makes "subject" a fundamental term in this ... References * Ahmad, K., M. Tariq, B. Vrusias and ...
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