期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2016
卷号：8
期号：07
页码：215-220
出版社：Engg Journals Publications
摘要：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.
