VISUAL SEARCH(*) OPTIMIZATION FOR NEAR DUPLICATE IMAGES
This theseis talks about visual search(*) optimization for near duplicate images. Visual search(*) mentioned is visual search implementation at eBay as explained by Yan, et al with limitation on the use of binary hashing to do visual search. This thesis explore optimization with that limitation....
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/51307 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | This theseis talks about visual search(*) optimization for near duplicate images.
Visual search(*) mentioned is visual search implementation at eBay as explained
by Yan, et al with limitation on the use of binary hashing to do visual search. This
thesis explore optimization with that limitation. This thesis tries to calculate near
duplicate based on hamming distance as implemented by Lin, et al based on the pre
calculated binary hash implemented by Yan, et al. Furthermore this thesis also try
to calculate near duplicate by modifying Hu, et al implementation by removing the
convolutional layer and use binary hash as the input instead of image. The result of
this thesis shows that the use of both approach to detect near duplicate is able to
give the expected result. Furtheermore, the hamming distance approach needs
shorter time for indexing |
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