Performance Analysis of Distance Metric for Content Based Image Retrieval
Divya M O1, Vimina E R2
1Divya M O, Assistant Professor, SCMS Cochin School of Business, Prathap Nagar, Muttom, Alwaye, Cochin.
2Vimina E R, Assistant Professor, Department of Computer Science & IT, Amrita School of Arts and Sciences, Kochi, Amrita Vishwa Vidyapeetham, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 2215-2218 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8610088619/2019©BEIESP | DOI: 10.35940/ijeat.F8610.088619
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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: Content based image retrieval uses different feature descriptors for image search and retrieval. For image retrieval from huge image repositories, the query image features are extracted and compares these features with the contents of feature repository. The most matching image is found and retrieved from the database. This mapping is done based on the distance calculated between feature vector of query image and the extracted feature vectors of images in the database. There are various distance measures used for comparing image feature vectors. This paper compares a set of distance measures using a set of features used for CBIR. The city-block distance measure gives the best results for CBIR.
Keywords: Distance measure, feature descriptors, image search, retrieval, cbir.