Content deleted Content added
m linking |
Neutronstar2 (talk | contribs) m →Texture |
||
| (9 intermediate revisions by 7 users not shown) | |||
Line 47:
}}</ref><ref name="Rui">{{cite journal|last1=Rui|first1=Yong|last2=Huang|first2=Thomas S.|last3=Chang|first3=Shih-Fu|title=Image Retrieval: Current Techniques, Promising Directions, and Open Issues|journal=Journal of Visual Communication and Image Representation|date=1999|volume=10|pages=39–62|doi=10.1006/jvci.1999.0413|citeseerx=10.1.1.32.7819|s2cid=2910032 }}{{dead link|date=September 2017 |bot=InternetArchiveBot |fix-attempted=yes }}</ref> Recent network- and graph-based approaches have presented a simple and attractive alternative to existing methods.<ref name="Banerjee">{{cite journal|last1=Banerjee, S. J.|display-authors=et al|title=Using complex networks towards information retrieval and diagnostics in multidimensional imaging|journal=Scientific Reports|date=2015|volume=5|pages=17271|doi=10.1038/srep17271|arxiv=1506.02602|pmid=26626047|pmc=4667282|bibcode=2015NatSR...517271B}}</ref>
While the storing of multiple images as part of a single entity preceded the term [[Object storage|BLOB]] ('''B'''inary '''L'''arge '''OB'''ject),<ref>{{cite web
|url=http://www.cvalde.net/misc/blob_true_history.htm
|archive-url=https://web.archive.org/web/20110723065224/http://www.cvalde.net/misc/blob_true_history.htm
Line 53:
|archive-date=2011-07-23
|title=The true story of BLOBs}}</ref> the ability to fully search by content, rather than by description, had to await IBM's QBIC.<ref name=IW.1996>{{cite magazine |magazine=[[InformationWeek|Information Week]] (OnLine-reprinted in Silicon Investor's Stock Discussion Forums (Aug. 6, 1996) |page=69 (IW) |author=Julie Anderson |date=April 29, 1996 |title=Search Images / Object Design Inc - Bargain of the year Stock Discussion Forums (Aug. 6, 1996) |url=https://www.siliconinvestor.com/readmsgs.aspx?subjectid=6903%26msgnum=17%26batchsize=10%26batchtype=Previous |quote=At DB Expo in San Francisco earlier this month ... }}{{Dead link|date=July 2019 |bot=InternetArchiveBot |fix-attempted=yes }}</ref>
=== VisualRank ===
{{excerpt|VisualRank}}
==Technical progress==
Line 77 ⟶ 79:
===Semantic retrieval===
''Semantic'' retrieval starts with a user making a request like "find pictures of Abraham Lincoln". This type of open-ended task is very difficult for computers to perform - Lincoln may not always be facing the camera or in the same [[pose (computer vision)|pose]]. Many CBIR systems therefore generally make use of lower-level features like texture, color, and shape. These features are either used in combination with interfaces that allow easier input of the criteria or with databases that have already been trained to match features (such as faces, fingerprints, or shape matching). However, in general, image retrieval requires human feedback in order to identify higher-level concepts.<ref name="Rui" />
===Relevance feedback (human interaction)===
Combining CBIR search techniques available with the wide range of potential users and their intent can be a difficult task. An aspect of making CBIR successful relies entirely on the ability to understand the user intent.<ref name="Ddata">{{cite journal | last=Datta | first=Ritendra |author2=Dhiraj Joshi |author3=Jia Li|author3-link=Jia Li |author4=James Z. Wang | title=Image Retrieval: Ideas, Influences, and Trends of the New Age | journal=ACM Computing Surveys | url=http://infolab.stanford.edu/~wangz/project/imsearch/review/JOUR/ | year=2008 | doi=10.1145/1348246.1348248 | volume=40 | issue=2 | pages=1–60| s2cid=7060187 }}</ref> CBIR systems can make use of ''[[relevance feedback]]'', where the user progressively refines the search results by marking images in the results as "relevant", "not relevant", or "neutral" to the search query, then repeating the search with the new information. Examples of this type of interface have been developed.<ref name="Bird"/>
===Iterative/machine learning===
Line 100 ⟶ 102:
Other methods of classifying textures include:
* [[Image texture#Co-occurrence Matrices|Co-occurrence matrix]]
* [[Image texture#Laws Texture Energy Measures|Laws texture energy]]
* [[Wavelet transform]]
* [[Orthogonal transform]]s (discrete
===Shape===
Shape does not refer to the shape of an image but to the shape of a particular region that is being sought out. Shapes will often be determined first applying [[Segmentation (image processing)|segmentation]] or [[edge detection]] to an image. Other methods use shape filters to identify given shapes of an image.<ref>{{cite book | last=Tushabe | first=F. |author2=M.H.F. Wilkinson | title=Advances in Multilingual and Multimodal Information Retrieval | chapter=Content-
Some shape descriptors include:<ref name="Rui"/>
Line 135 ⟶ 137:
* Photograph archives
* Retail catalogs
* Nudity-detection filters<ref>{{cite journal | last=Wang |first = James Ze |author2=Jia Li |author2-link=Jia Li|author3=Gio Wiederhold |author4=Oscar Firschein|title=System for Screening Objectionable Images|journal=Computer Communications|year = 1998|volume=21|issue=15|pages=1355–1360|doi=10.1016/s0140-3664(98)00203-5|citeseerx = 10.1.1.78.7689 }}</ref>
* [[Facial recognition system|Face Finding]]
* Textiles Industry<ref name="Bird">{{cite conference | last=Bird | first=C.L. | author2=P.J. Elliott |author3=E. Griffiths | title=User interfaces for content-based image retrieval |book-title=IEE Colloquium on Intelligent Image Databases |publisher=IET |doi=10.1049/ic:19960746 |date=1996}}</ref>
Line 189 ⟶ 191:
* ''[https://doi.org/10.1007%2F3-540-45479-9_17 FACERET: An Interactive Face Retrieval System Based on Self-Organizing Maps]'' (Ruiz-del-Solar et al., 2002)
* ''[http://www-db.stanford.edu/~wangz/project/imsearch/ALIP/PAMI03/ Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach]'' (Li and Wang, 2003)
* ''[
* ''[http://www.svcl.ucsd.edu/publications/journal/2004/sp04/sp04.pdf Minimum Probability of Error Image Retrieval]'' (Vasconcelos, 2004)
* ''[http://www.svcl.ucsd.edu/publications/journal/2004/it04/it04.pdf On the Efficient Evaluation of Probabilistic Similarity Functions for Image Retrieval]'' (Vasconcelos, 2004)
Line 224 ⟶ 226:
* [https://www.springer.com/13735 IJMIR] many CBIR-related articles
* [http://www.sepham.com/ Search by Drawing]
* [https://web.archive.org/web/20120518124442/http://pixolution.does-it.net/fileadmin/template/visual_web_demo.html Demonstration of a visual search engine for images. (Search by example image or colors)]2.242654
{{DEFAULTSORT:Content-Based Image Retrieval}}
| |||