Content Based Image Retrieval: A Review
Ramandeep Kaur1, V. Devendran2
1Ramandeep Kaur, Lovely Professional University, Phagwara, Punjab, India.
2Dr. V. Devendran, Professor, Lovely Professional University, Phagwara, Punjab, India.
Manuscript received on July 13, 2020. | Revised Manuscript received on July 26, 2020. | Manuscript published on August 10, 2020. | PP: 222-228 | Volume-9 Issue-10, August 2020 | Retrieval Number: 100.1/ijitee.J74530891020 | DOI: 10.35940/ijitee.J7453.0891020
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image recovery was one of the most thrilling and vibrant fields of computer vision science. Content-based image retrieval systems (CBIR) are used to catalog, scan, download and access image databases automatically. Color & texture features are significant properties for content-based image recovery systems. The content-based image retrieval (CBIR) is therefore an attractive source of accurate and quick retrieval. Number of techniques has been established in recent years to improve the performance of CBIR. This paper discusses why CBIR is important nowadays along with the limitations and benefits. Apart from applications, various feature extraction techniques used in CBIR are also discussed.
Keywords: Image recovery, Image Processing, CBIR, Feature Extraction.
Scope of the Article: Image analysis and Processing