On the working principle of search engine for different forms of image

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What we often say is the article in the website. Text of the promotion and optimization, today with you say that search engine for different forms of image working principle, so for everyone to do after the image of the SEO work is very instructive. At present, most of the mainstream image search engine, the text link or the image of the ALT description tag and other HTML elements to identify the image content, of course, there are based on the content of the picture itself to do the image content to explore. Now let's look at two different types of images for analysis.

1. Image search engine using text and other third party factors to distinguish picture content

When a search engine crawler (spider) Searches for a new page in the web via a URL, it extracts the page via the HTTP protocol and transmits the HTML code of the page to the Content Analyzer. Content analysis looks for images contained in a Web page based on pending HTML code, such as <img> tags.

The search engine crawler then determines the content of the image based on the title, heading, Keyworlds, description tag in the HTML code of the page and the <alt> attribute in the <img> tag. At the same time, the SE crawler also determines the content of the image by linking to the external link to the page. When the search engine can basically judge the content of the picture, it will be summarized according to the content of the picture, and the correlation degree of the picture and the keyword is sorted,

After we have identified the content of the picture, the classification, the search engine will be the analysis of good data into the index database, and automatically generate thumbnails for the picture. When the user search, the search engine will be based on the picture content, relevance and other factors to the image sequence, and ultimately more accurate and relevant results to show the user.

2. Search engine to determine image content by analyzing picture itself

At present through the content of the picture itself content analysis of the search engine is not many, mainly some foreign. One of the notable is the University of Washington's Chuck Jacobs, Adan Finkelstein and David Salesin and the RETRIEVR system introduced in 2005. The network display address of RETRIEVR system is: http:labs.systemone.at/retrievr/.

The image content of the RETRIEVR system is from the images uploaded by www.flickr.com website users. The principle of the system is basically this: to each Flickr user uploaded images to the color map similarity analysis, and the use of color map and map differences to classify the picture. When the user is searching, only need to draw a certain shape on the graffiti board of the RETRIEVR system, the system can automatically make the pictures similar to the graffiti recommended to the user, the specific interface you can look at the following figure.

The search engine based on chromatographic deviation for image analysis is basically in the research stage, especially in China. So for our Chinese search engine, this piece is still very immature. And the current mainstream search engine in doing image analysis mostly rely on the analysis of HTML code, to determine the image you want to promote out. So this piece for our Chinese webmaster, we only as understanding.

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