Image Retrieval using Associativity between ABIR and CBIR Features
Journal Title: International Journal on Computer Science and Engineering - Year 2016, Vol 8, Issue 7
Abstract
The present paper provides the information about image retrieval using the concept of Attribute Base Image Retrieval (ABIR) and (CBIR) Content Base Image Retrieval and the fusion of both method (visual and textual) which is a recent course in image retrieval researches. For CBIR we used the Scale-Invariant Feature Transform (SIFT) technique. ABIR is annotation based technique. For fusion of both ABIR and CBIR we used APRIORI algorithm.Using that algorithm we get the one result from above two results (results from ABIR and CBIR).In that algorithm it find out the relationship between visual and textual form, and then generate the result. SIFT joins two different data mining techniques to get semantically related images these are: association and clustering rules mining algorithm which is nothing but the Bag of Features (BoF). BoF methods are based on order less collection of quantized local image descriptors they remove spatial information and are therefore computationally and conceptually simpler than many alternative methods. Apriori is an algorithm for regular item set mining then association rule learning above transactional databases. Apriori is designed to operate on databasescontaining transactions.
Authors and Affiliations
Swati L. Dudhe , Prof. Sonali Bodkhe
Keywords
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