Content-based image retrieval General scheme of content-based image retrieval Content-based image retrieval (CBIR), 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 survey[1] for a recent scientific overview of the CBIR field). Content-based image retrieval is opposed to traditional concept-based approaches (see concept-based image indexing). History[edit] The term "content-based image retrieval" seems to have originated in 1992 when it was used by T. The earliest commercial CBIR system was developed by IBM and was called QBIC (Query by Image Content).[3] Technical progress[edit] The interest in CBIR has grown because of the limitations inherent in metadata-based systems, as well as the large range of possible uses for efficient image retrieval. CBIR techniques[edit] Query techniques[edit] Color[edit] Shape[edit]
Qrobe - Search Engine imgSeek Quick Screen Capture tool. Take Screenshots, Edit and Share them List of academic databases and search engines From Wikipedia, the free encyclopedia This article contains a representative list of notable databases and search engines useful in an academic setting for finding and accessing articles in academic journals, institutional repositories, archives, or other collections of scientific and other articles. Databases and search engines differ substantially in terms of coverage and retrieval qualities.[1] Users need to account for qualities and limitations of databases and search engines, especially those searching systematically for records such as in systematic reviews or meta-analyses.[2] As the distinction between a database and a search engine is unclear for these complex document retrieval systems, see: the general list of search engines for all-purpose search engines that can be used for academic purposesthe article about bibliographic databases for information about databases giving bibliographic information about finding books and journal articles. Operating services[edit] [edit] [edit]
Image Recognition and Visual Search 9 OCR gratuits, en ligne et sans logiciel L’OCR c’est la reconnaissance optique des caractères. Si vous scannez un texte, le résultat vous arrivera sous forme de photo, il va donc falloir que vous passiez par un logiciel OCR qui transformera ces photos en texte. Ce texte pourra ensuite être modifié plus facilement via un logiciel de traitement de teste. Voilà une sélection de 12 sites OCR gratuits en ligne. Ce service est réellement simple, rapide et surtout ne nécessite pas de création de compte, ni d’envoi par email. L’avantage du service OCR de google drive ou appelons le aussi Google doc, c’est qu’en plus de la reconnaissance de caractères, on vous propose de sauvegarder le fichier et ensuite, de pouvoir faire une recherche pour retrouver le document en question. Selon le blogue de blogs.windows.com il est possible de convertir les fichiers photos en texte via un le service skydrive. En ligne et rapide;les trois étapes classiques, chargement du fichier, choix du format de sortie et conversion Newocr.com (simple) versions
99 Resources to Research & Mine the Invisible Web College researchers often need more than Google and Wikipedia to get the job done. To find what you're looking for, it may be necessary to tap into the invisible web, the sites that don't get indexed by broad search engines. The following resources were designed to help you do just that, offering specialized search engines, directories, and more places to find the complex and obscure. Search Engines Whether you're looking for specific science research or business data, these search engines will point you in the right direction. Turbo10: On Turbo10, you'll be able to search more than 800 deep web search engines at a time. Databases Tap into these databases to access government information, business data, demographics, and beyond. GPOAccess: If you're looking for US government information, tap into this tool that searches multiple databases at a time. Catalogs If you're looking for something specific, but just don't know where to find it, these catalogs will offer some assistance. Directories
Image Enrichment Technologies Java Project Image Enrichment Technologies Projects main idea is to demonstrate different image sharpening techniques and how filters can be used for improving quality of image in digital computer technology. Improving the quality of message include three methods, sharpening, smoothening and reducing noise. In present system usage of digital image processing has rapidly increased because of digital computing. Main aim of using digital image processing methods is to enhance picture information for human interpretation. Removing noise from digital image is one of the widely used technique for improving quality of picture, this is done using filters and filters are also used in other techniques like image sharpening and smoothening. This application is implemented using java technology because of its universal acceptance and easy understanding. download Image Enrichment Technologies Java Project The following two tabs change content below. ‹‹‹ Dealer Based Network Business System Project Custom Search