Ornament Image Retrieval Using Multimodal Fusion
Search-by-example, i.e. finding images that are similar to a query image, is an indispensable function for various modern image search engines. The applications of such systems are manifold. The primary application of search-by-example is in recommending fashion materials based on user interests. Th...
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| Veröffentlicht in: | SN computer science 2021-07, Vol.2 (4), p.336, Article 336 |
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| creator | Islam, Sk Maidul Joardar, Subhankar Dogra, Debi Prosad Sekh, Arif Ahmed |
| description | Search-by-example, i.e. finding images that are similar to a query image, is an indispensable function for various modern image search engines. The applications of such systems are manifold. The primary application of search-by-example is in recommending fashion materials based on user interests. There are various challenges in this area of research such as a large volume of the product database, similar visual appearances, and a large variety of products. The problem becomes more difficult to solve when the product is complex in design such as ornaments. In this paper, we have proposed a fusion-based retrieval model. The method uses weighted average of multiple similarity measures. We have used four different methods namely hash-based, histogram-based, deep feature comparison, and feature cross correlation to find the similarity. A dataset of ornaments (golden earrings) has been prepared and made available to the research community. We achieve 81% top-1 and 89% top-5 accuracy using the proposed method. The dataset and the code is available publicly in
https://github.com/skarifahmed/RingFIR
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| doi_str_mv | 10.1007/s42979-021-00734-1 |
| format | Article |
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https://github.com/skarifahmed/RingFIR
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https://github.com/skarifahmed/RingFIR
.</description><subject>Artificial intelligence</subject><subject>Computer Imaging</subject><subject>Computer Science</subject><subject>Computer Systems Organization and Communication Networks</subject><subject>Cross correlation</subject><subject>Data Structures and Information Theory</subject><subject>Datasets</subject><subject>Deep learning</subject><subject>Fashion</subject><subject>Histograms</subject><subject>Image retrieval</subject><subject>Information Systems and Communication Service</subject><subject>Neural networks</subject><subject>Original Research</subject><subject>Pattern Recognition and Graphics</subject><subject>Popularity</subject><subject>Recommender systems</subject><subject>Retrieval</subject><subject>Search engines</subject><subject>Semantics</subject><subject>Similarity</subject><subject>Software Engineering/Programming and Operating Systems</subject><subject>Vision</subject><issn>2662-995X</issn><issn>2661-8907</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kEtLAzEUhYMoWGr_gKsB19F785pkKcVqoVIQC-5COpOWKfOoyYzgvzftCO5c3QfnHA4fIbcI9wiQP0TBTG4oMKTp5ILiBZkwpZBqA_nleWfUGPlxTWYxHgCASRBCyQmBdWhd49s-WzZu77M334fKf7k628Sq3WevQ91XTVemx2KIVdfekKudq6Of_c4p2Sye3ucvdLV-Xs4fV7RAJZAqU3q942zrPOYCS3QMGAjtlEtlsfDKbB14bZzPmZGukKWRqkTNpZJCcD4ld2PuMXSfg4-9PXRD6lpHywxnudYcTio2qorQxRj8zh5D1bjwbRHsCY4d4dgEx57hWEwmPppiErd7H_6i_3H9AFaIZOY</recordid><startdate>20210701</startdate><enddate>20210701</enddate><creator>Islam, Sk Maidul</creator><creator>Joardar, Subhankar</creator><creator>Dogra, Debi Prosad</creator><creator>Sekh, Arif Ahmed</creator><general>Springer Singapore</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0003-2470-1269</orcidid></search><sort><creationdate>20210701</creationdate><title>Ornament Image Retrieval Using Multimodal Fusion</title><author>Islam, Sk Maidul ; Joardar, Subhankar ; Dogra, Debi Prosad ; Sekh, Arif Ahmed</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1641-69de8f32bae1741d1a202048a6a2971ce69ba0e89ae7295ac5d956d1835654433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Artificial intelligence</topic><topic>Computer Imaging</topic><topic>Computer Science</topic><topic>Computer Systems Organization and Communication Networks</topic><topic>Cross correlation</topic><topic>Data Structures and Information Theory</topic><topic>Datasets</topic><topic>Deep learning</topic><topic>Fashion</topic><topic>Histograms</topic><topic>Image retrieval</topic><topic>Information Systems and Communication Service</topic><topic>Neural networks</topic><topic>Original Research</topic><topic>Pattern Recognition and Graphics</topic><topic>Popularity</topic><topic>Recommender systems</topic><topic>Retrieval</topic><topic>Search engines</topic><topic>Semantics</topic><topic>Similarity</topic><topic>Software Engineering/Programming and Operating Systems</topic><topic>Vision</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Islam, Sk Maidul</creatorcontrib><creatorcontrib>Joardar, Subhankar</creatorcontrib><creatorcontrib>Dogra, Debi Prosad</creatorcontrib><creatorcontrib>Sekh, Arif Ahmed</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>SN computer science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Islam, Sk Maidul</au><au>Joardar, Subhankar</au><au>Dogra, Debi Prosad</au><au>Sekh, Arif Ahmed</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Ornament Image Retrieval Using Multimodal Fusion</atitle><jtitle>SN computer science</jtitle><stitle>SN COMPUT. 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We have used four different methods namely hash-based, histogram-based, deep feature comparison, and feature cross correlation to find the similarity. A dataset of ornaments (golden earrings) has been prepared and made available to the research community. We achieve 81% top-1 and 89% top-5 accuracy using the proposed method. The dataset and the code is available publicly in
https://github.com/skarifahmed/RingFIR
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| subjects | Artificial intelligence Computer Imaging Computer Science Computer Systems Organization and Communication Networks Cross correlation Data Structures and Information Theory Datasets Deep learning Fashion Histograms Image retrieval Information Systems and Communication Service Neural networks Original Research Pattern Recognition and Graphics Popularity Recommender systems Retrieval Search engines Semantics Similarity Software Engineering/Programming and Operating Systems Vision |
| title | Ornament Image Retrieval Using Multimodal Fusion |
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