NDLI: Spatially related image mining on very large image collections

Content Provider	IEEE Xplore Digital Library
Author	Emymal, S.N. Yesubai Rubavathi, C.
Copyright Year	2011
Description	Author affiliation: Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India (Emymal, S.N.) \|\| CSE dept., Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India (Yesubai Rubavathi, C.)
Abstract	Collections of images of ever growing sizes are becoming common. Structuring and browsing large image databases is a challenging problem. Access to images based on the 3D acquisition location or on the spatial overlap of the scenes they depict is intuitive and has high user acceptability. Commonly, the sets of relevant spatially related images are obtained using manual annotations. A method for discovering spatial overlaps using image content only via image retrieval techniques was proposed. The objective of the proposed approach is to provide a randomized data mining method for finding clusters of images with spatial overlap. Instead of trying to match each image, in turn, the method relies on the min- Hash algorithm for fast detection of random pairs of images with spatial overlap, the so-called cluster seeds. The seeds are then used as visual queries and clusters are obtained as transitive closures of sets of partially overlapping images that include the seed. This approach shows that the probability of finding a seed for an image cluster rapidly increases with the size of the cluster and approaches one fast. For practical database sizes, the running time of the seed generation process is close to linear in the size of the database. The cluster completion process requires a number of visual queries proportional to the number of images in all clusters. The proposed method discovers the spatially related images in large-scale image databases.
Starting Page	864
Ending Page	869
File Size	1195217
Page Count	6
File Format	PDF
ISBN	9781424479238
e-ISBN	9781424479269
DOI	10.1109/ICETECT.2011.5760240
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-03-23
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cluster seed Visualization Vocabulary Bag of words Image edge detection Image retrieval Image clustering Spatial databases Data mining Min Hash
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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