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Capturing data can be done in various ways; the best method depends on application. In biometric security systems, capture is the acquisition of or the process of acquiring and identifying characteristics such as finger image, palm image, facial image, iris print, or voiceprint which involves audio data, and the rest all involve video data.
File renaming, single-click background copy/move to preset location, single-click rating/labeling (writes Adobe XMP sidecar files and/or embeds XMP metadata within JPEG/TIFF/HD Photo/JPEG XR), Windows rating, color management including custom target profile selection, Unicode support, Exif shooting data (shutter speed, f-stop, ISO speed ...
Pictures of objects. Detailed object outlines marked. 9146 Images Classification, object recognition 2003 [32] [33] F. Li et al. Caltech-256 Large dataset of images for object classification. Images categorized and hand-sorted. 30,607 Images, Text Classification, object detection 2007 [34] [35] G. Griffin et al. COYO-700M Image–text-pair dataset
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.
Two main options can be used to geotag photos: capturing GPS information at the time the photo is taken or "attaching" geocoordinates to the photograph after the picture is taken. In order to capture GPS data at the time the photograph is captured, the user must have a camera with built in GPS or a standalone GPS along with a digital camera.
Metadata Working Group was formed by a consortium of companies in 2006 (according to their web page) or 2007 (as stated in their own press release). Version 2.0 of the specification was released in November 2010, [8] giving recommendations concerning the use of Exif, IPTC and XMP metadata in images.
General scheme of content-based image retrieval. Content-based image retrieval, also known as query by image content 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 scientific overview of the CBIR field).
Because attributes are defined by metadata, CMDBs also contain metadata, and thus the concept overlaps with that of a metadata repository, which is also used to more effectively run IT organizations. Configuration management addresses how the data is to be kept up to date. This has historically been a weakness of metadata repositories.
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