CONTENT-BASED IMAGE RETRIEVAL: SURVEY
Extensive use of digital photographic devices has resulted in large volumes of digital images being acquired and stored in databases. Whether it is for scientific research, medical or social networking, there is a growing demand for effective retrieval of digital images based on their visual conten...
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| Format: | Article |
| Language: | Arabic |
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Mustansiriyah University/College of Engineering
2019-05-01
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| Series: | Journal of Engineering and Sustainable Development |
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| Online Access: | https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/254 |
| _version_ | 1798022539483545600 |
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| author | Hanan Ahmed Al-Jubouri |
| author_facet | Hanan Ahmed Al-Jubouri |
| author_sort | Hanan Ahmed Al-Jubouri |
| collection | DOAJ |
| description |
Extensive use of digital photographic devices has resulted in large volumes of digital images being acquired and stored in databases. Whether it is for scientific research, medical or social networking, there is a growing demand for effective retrieval of digital images based on their visual content (e.g. colour and texture). Content-Based Image Retrieval systems are developed to meet this demand. However, searching for similar and relevant images from large-scale databases still poses a challenge for Content-Based Image Retrieval systems due to the gap between high-level meaning and low-level visual features. This paper reviews different Content-Based Image Retrieval approaches such as Clustering, Region-of-Interest, Bag-of-Visual-Words, Relevance Feedback, Browsing, and indexing that have been developed to reduce such “Semantic gap” issue. So, the interested researchers can interest to determine which method is benefit to his work.
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| first_indexed | 2024-04-11T17:31:41Z |
| format | Article |
| id | doaj.art-db310939e13e471b9208655060de630b |
| institution | Directory Open Access Journal |
| issn | 2520-0917 2520-0925 |
| language | Arabic |
| last_indexed | 2024-04-11T17:31:41Z |
| publishDate | 2019-05-01 |
| publisher | Mustansiriyah University/College of Engineering |
| record_format | Article |
| series | Journal of Engineering and Sustainable Development |
| spelling | doaj.art-db310939e13e471b9208655060de630b2022-12-22T04:11:59ZaraMustansiriyah University/College of EngineeringJournal of Engineering and Sustainable Development2520-09172520-09252019-05-01233CONTENT-BASED IMAGE RETRIEVAL: SURVEYHanan Ahmed Al-Jubouri0 Computer Engineering Department, Mustansiriyah University, Baghdad, Iraq Extensive use of digital photographic devices has resulted in large volumes of digital images being acquired and stored in databases. Whether it is for scientific research, medical or social networking, there is a growing demand for effective retrieval of digital images based on their visual content (e.g. colour and texture). Content-Based Image Retrieval systems are developed to meet this demand. However, searching for similar and relevant images from large-scale databases still poses a challenge for Content-Based Image Retrieval systems due to the gap between high-level meaning and low-level visual features. This paper reviews different Content-Based Image Retrieval approaches such as Clustering, Region-of-Interest, Bag-of-Visual-Words, Relevance Feedback, Browsing, and indexing that have been developed to reduce such “Semantic gap” issue. So, the interested researchers can interest to determine which method is benefit to his work. https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/254Bag-of-Visual-WordsBrowsingClusteringContent-Based Image RetrievalRelevance FeedbackRegion-of- Interest |
| spellingShingle | Hanan Ahmed Al-Jubouri CONTENT-BASED IMAGE RETRIEVAL: SURVEY Journal of Engineering and Sustainable Development Bag-of-Visual-Words Browsing Clustering Content-Based Image Retrieval Relevance Feedback Region-of- Interest |
| title | CONTENT-BASED IMAGE RETRIEVAL: SURVEY |
| title_full | CONTENT-BASED IMAGE RETRIEVAL: SURVEY |
| title_fullStr | CONTENT-BASED IMAGE RETRIEVAL: SURVEY |
| title_full_unstemmed | CONTENT-BASED IMAGE RETRIEVAL: SURVEY |
| title_short | CONTENT-BASED IMAGE RETRIEVAL: SURVEY |
| title_sort | content based image retrieval survey |
| topic | Bag-of-Visual-Words Browsing Clustering Content-Based Image Retrieval Relevance Feedback Region-of- Interest |
| url | https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/254 |
| work_keys_str_mv | AT hananahmedaljubouri contentbasedimageretrievalsurvey |