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List Of CBIR Engines
This is a list of publicly available Content-based image retrieval (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 , , University , Closed , - Anaktisi, This Web-Solution implements a new family of CBIR descriptors. These descriptors combine in one histogram color and texture information and are suitable for accurately retrieving images. , Yes , No , 0.225M , University , ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 for digital images in large databases (see this surveyContent-based Multimedia Information Retrieval: State of the Art and Challenges' (Original source, 404'''Content-based Multimedia Information Retrieval: State of the Art and Challenges'', Michael Lew, et al., ACM Transactions on Multimedia Computing, Communications, and Applications, pp. 1–19, 2006. for a scientific overview of the CBIR field). Content-based image retrieval is opposed to traditional concept-based approaches (see Concept-based image indexing). "Content-based" means that the search analyzes the contents of the image rather than the metadata such as keywords, tags, or descriptions associated with the image. The term "content" in this context might refer to colors, sha ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reverse Image Search
Reverse image search is a content-based image retrieval (CBIR) query technique that involves providing the CBIR system with a sample image that it will then base its search upon; in terms of information retrieval, the sample image is very useful in its ways. In particular, reverse image search is characterized by a lack of search terms. This effectively removes the need for a user to guess at keywords or terms that may or may not return a correct result. Reverse image search also allows users to discover content that is related to a specific sample image, popularity of an image, and discover manipulated versions and derivative works. Uses Reverse image search may be used to: * Locate the source of an image. * Find higher resolution versions. * Discover webpages where the image appears. * Find the content creator. * Get information about an image. Algorithms Commonly used reverse image search algorithms include: * Scale-invariant feature transform - to extract local features of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google Custom Search
Google Programmable Search Engine (formerly known as Google Custom Search and Google Co-op) is a platform provided by Google that allows web developers to feature specialized information in web searches, refine and categorize queries and create customized search engines, based on Google Search. The service allows users to narrow the 11.5 billion Web indexing, indexed webpages down to a topical group of pages relevant to the creator's needs. Google launched the service on October 23, 2006. Services The Google Custom Search platform consists of three services: Custom Search Engine Released on October 23, 2006, Google Programmable Search allows anyone to create their own search engine by themselves. Search engines can be created to search for information on particular topics chosen by the creator. Google Programmable Search Engine allows creators to select what websites will be used to search for information which helps to eliminate any unwanted websites or information. Creators ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Getty Images
Getty Images Holdings, Inc. is an American visual media company and is a supplier of stock images, editorial photography, video and music for business and consumers, with a library of over 477 million assets. It targets three markets— creative professionals (advertising and graphic design), the media (print and online publishing), and corporate (in-house design, marketing and communication departments). Getty Images has distribution offices around the world and capitalizes on the Internet for distribution with over 2.3 billion searches annually on its sites. As Getty Images has acquired other older photo agencies and archives, it has digitised their collections, enabling online distribution. Getty Images operates a large commercial website that clients use to search and browse for images, purchase usage rights, and download images. Image prices vary according to resolution and type of rights. The company also offers custom photo services for corporate clients. History In ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Macroglossa Visual Search
Macroglossa was a visual search engine based on the comparison of images, coming from an Italian Group. The development of the project began in 2009. In April 2010 is released the first public alpha. Users can upload photos or images that they aren't sure what they are to determine what the images contain. Macroglossa compares images to return search results based on specific search categories. The engine does not use technologies and solutions such as OCR, tags, vocabulary trees. The comparison is directly based on the contents of the image which the user wants to know more. Included features are the categorization of the elements, the ability to search specific portions of the image or start a search from a video file, but the main function is to simulate a digital eye on trying to find similarities of an unknown subject. This technology allows users to pull results from collections of visual content without using tags for search. The visuals can be crowd sourced. In addition, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 methods ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
