Index construction method for distributed picture search and server

Abstract

The invention discloses an index construction method for distributed picture search and a device. The index construction method comprises the following steps of: extracting more than one feature of all pictures in a picture database of the server, and converting the features into a sight word set to obtain an original sight word dictionary and a total index table corresponding to the original sight word dictionary; acquiring an effective sight word dictionary representing the original sight word dictionary, wherein each sight word in the effective sight word dictionary is built with a respective corresponding inverted record table; and uniformly distributing each sight word in the effective sight word dictionary to each index server by adopting a first preset rule so that each index server obtains a sub sight word dictionary consisting of the sight words therein and the inverted record tables of the sight words in the sub sight word dictionary form an index table of the sub sight word dictionary. The method can improve the index efficiency of the server and meet the real-time response requirement on a user in searching.

Description

Technical field [0001] The present invention relates to the field of picture search, in particular to an index construction method, server, picture search method and picture search system for distributed picture search. Background technique [0002] In recent years, there have been a large number of research results on visual retrieval methods that directly use pictures to search at home and abroad, and visual search has become a hot application in industrial fields such as smart phones and e-commerce. [0003] However, it takes a long time to search for visual features in massive image databases, mainly due to the large number of massive image databases brought by Internet applications, resulting in the entire image database’s inverted index files far exceeding a single The memory capacity of the server; further, the inverted index is completely stored in the memory of a single server, and it will take a long search time to find the result image in a huge single inverted index, wh...

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Problems solved by technology

[0003]However, it takes a long time to retrieve visual features in massive image databases, mainly due to the emergence of massive image databases brought about by Internet applications, resulting in The inverted index file of the entire image database is far beyond the memory capacity of a single server; furthermore, the inverted index is completely stored in the memory of a single server, and it will take a long time to find the resulting image in a huge single inverted index The search time is too long, it is difficult to meet the user's requirements for search speed, let alone meet the user's real-time response retrieval needs

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