DocumentCode :
541747
Title :
Attribute associated image retrieval and similarity reranking
Author :
Abubacker, K. A Shaheer ; Indumathi, L.K.
Author_Institution :
Dept. of Comput. Sci. & Eng., Nat. Coll. of Eng., Tirunelveli, India
fYear :
2010
fDate :
27-29 Dec. 2010
Firstpage :
235
Lastpage :
240
Abstract :
Existence of countless digital images has given rise to image retrieval in many applications. Conventional image databases being text-annotated pose two major problems of keywords for images and complexity. Hence, retrieval systems based on image´s visual content are more desirable [1]. The content based image retrieval (CBIR) technique, employed here uses visual cues to retrieve images. This technique is query based, extracts the most vital attributes like color, shape and texture. Automatic extraction of spatial based color feature and invariant Fourier descriptors makes it more flexible. The extent of each attribute is obtained from the user, compared with attributes of images in database and most similar images are retrieved based on the degree of similarity.
Keywords :
content-based retrieval; feature extraction; image colour analysis; image matching; image retrieval; image texture; shape recognition; text analysis; visual databases; attribute associated image retrieval; color feature extraction; content based image retrieval; digital image database; invariant Fourier descriptor; query based technique; shape attribute; similarity reranking; text annotated pose; texture attribute; Feature extraction; Gabor filters; Image color analysis; Image retrieval; Pixel; Shape; Visualization; CBIR; Gabor filter; Image Retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication and Computational Intelligence (INCOCCI), 2010 International Conference on
Conference_Location :
Erode
Type :
conf
Filename :
5738736
Link To Document :
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