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Google Images
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Google Images is a search service owned by Google and introduced in July 2001, that allows users to search the Web for image content.[1] The keywords for the image search are based on the filename of the image, the link text pointing to the image, and text adjacent to the image. When searching for an image, a thumbnail of each matching image is displayed. When the user clicks on a thumbnail, the image is displayed in a box over the website that it came from. The user can then close the box and browse the website, or view the full-sized image.In 2001, 250 million images were indexed. In 2005, this grew to 1 billion. By 2010, the index reached 10 billion images.[2] As of July 2010, the service receives over one billion views a day.[3] Google introduced a sort by subject feature for a visual category scheme overview of a search query in May 2011.[4]In early 2007 Google implemented an updated user interface for the image search, where information about the image, such as resolution and URL, was hidden until the user moved the mouse over the thumbnail.[5] This was discontinued after a few weeks.

On October 27, 2009, Google Images added a feature to its image search that can be used to find similar images.[6][7]

On July 20, 2010, Google updated the user interface again, hiding image details until mouse over, like before.[8] This feature can be disabled by pressing "Ctrl + End" on one's keyboard and clicking "Switch to basic version".

In June 2011, Google Images began to allow for reverse image searches directly in the image search-bar (that is, without a third-party add on, such as the one previously available for Mozilla Firefox). This feature allows users to search by dragging and dropping an image into the search-bar, uploading an image, selecting a URL, or 'right-clicking' on an image.

On December 11, 2012, Google Images' search engine algorithm was changed once again, in the hopes of preventing pornographic images from appearing when non-pornographic search terms are used.[10][11][12] According to Google, pornographic images would still appear as long as the term searched for was specifically pornographic. While explicitly stating that they were "not censoring any adult content", it was immediately noted that even when entering terms such as "blow job",[12][13] "boob,"[12] or even the word "pornography" itself, no explicit results were shown. The only alternative option is to turn on an even stricter filter which will refuse to search for the aforementioned terms whatsoever. It has also been noted that users can no longer exclude keywords from their search as before.[14]

Image collection exploration is a mechanism to explore large digital image repositories. The huge amount of digital images produced every day through different devices such as mobile phones bring forth challenges for the storage, indexing and access to these repositories. Content-based image retrieval (CBIR) has been the traditional paradigm to index and retrieve images. However, this paradigm suffers of the well known semantic gap problem. Image collection exploration consists of a set of computational methods to represent, summarize, visualize and navigate image repositories in an efficient, effective and intuitive way.[1]

Automatic summarization consists in finding a set of images from a larger image collection that represents such collection.[2] Different methods based on clustering have been proposed to select these image prototypes (summary). The summarization process addresses the problem of selecting a representative set of images of a search query or in some cases, the overview of an image collection.[3]
Image collection visualization is the process of visualize a set of images using a visualization metaphor, in which an image similarity function is used to represent image relations in a visualization layout.[4] Information visualization is an active area that investigates new ways to visualize information by using visualization metaphors. Particularly, new ways of visualizing image collections are being investigated, which propose conventional [5] and unconventional [6] visualization metaphors.Image collection interaction consists in offering users mechanisms to feedback image search systems.[7] In this interaction process, the system learns from user feedback to retrieve results more precise and relevant to the user.

Google Images Search Flowers Logo Advanced Tattoos Upload Flowers Roses Valentines Day Download Gravity