Image search is a particular data search used to find images. To search for images, a user may give query terms such as keyword, image file/link, or click on some image, and the system will return images "similar" to the query. In this system Internet image search approach which only needs one-click user response. Intention specific weight schema is proposed to combine visual features and to compute visual similarity adaptive to query images.
In Existing system, one way is text-based keyword expansion, making the textual description of the query more detailed. Existing linguistically-related methods find either synonyms or other linguistic-related words from thesaurus, or find words frequently co occurring with the query keywords.
No data analysis
In Proposed system, we propose an image search approach. It requires the user to give only one click on a query image and images from a pool retrieved by text based search are re-ranked based on their visual and textual similarities to the query image. We believe that users will tolerate one-click interaction which has been used by many popular text-based search engines. For example, Google requires a user to select a suggested textual query expansion by one-click to get additional results. The key problem to be solved in this system is how to capture user intention from this one-click query image.
PROPOSED SYSTEM TECHNIQUE:
Multi-Layer Rotation Invariant EOH
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