2016 International Conference on Emerging Technological Trends (ICETT) 2016
DOI: 10.1109/icett.2016.7873663
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Fast image retrieval using error diffusion block truncation coding and unsupervised clustering

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Cited by 7 publications
(6 citation statements)
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“…The velocity of retrieval varies parallel with the wide variety of pictures in the database i.e. An increase in database images confirmed good sized increase in the machine overall performance [7].…”
Section: Letrature Surveymentioning
confidence: 83%
“…The velocity of retrieval varies parallel with the wide variety of pictures in the database i.e. An increase in database images confirmed good sized increase in the machine overall performance [7].…”
Section: Letrature Surveymentioning
confidence: 83%
“…When the user asks the query, then it will be matched with the database and retrieve the image. It retrieves the exact image by comparing the texture, color, and shape [3]. The color images are indexed using the features extracted from Error Diffusion Block Truncation Coding (EDBTC).…”
Section: Introductionmentioning
confidence: 99%
“…The speed of retrieval varies linearly with the number of images in the database i.e. an increase in database images showed significant increase in the system performance [11].…”
Section: Literature Surveymentioning
confidence: 99%
“…Also, the proposed method achieves the improvement of 13% and 2% in precision and recall, respectively, in comparison with prior methods [10]. Devi S, et al [2016] In this paper color descriptions are indexed using the features extracted from Error Diffusion Block Truncation Coding (EDBTC). A new framework of CBIR with unsupervised clustering is used here in which the amount of time required for comparing the target and query image is significantly reduced.…”
Section: Literature Surveymentioning
confidence: 99%