Relevance Feedback Techniques Implemented in CBIR: Current Trends and Issues

Sheshasaayee, Ananthi; Jasmine, C.

doi:10.14445/22315381/ijett-v10p232

Cited by 8 publications

(2 citation statements)

References 9 publications

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“…This problem has served as the momentum for what is identified as ''RF.'' RF retrieval system 24,37,38 is used to increase the retrieval performance by prompting the user for feedback based on retrieval results.…”

Section: Interactive Rfmentioning

confidence: 99%

“…The results are designed to be unsatisfactory based on the significant divergence between the opinion of similarity in the user’s mind and the similarity as calculated by the system. This problem has served as the momentum for what is identified as “RF.” RF retrieval system 24,37,38 is used to increase the retrieval performance by prompting the user for feedback based on retrieval results.…”

Section: Modified Binary Wavelet Transform–based Histogrammentioning

confidence: 99%

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Combined global and local semantic feature–based image retrieval analysis with interactive feedback

Anandh

Mala²,

Babu

2019

Measurement and Control

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Nowadays, user expects image retrieval systems using a large database as an active research area for the investigators. Generally, content-based image retrieval system retrieves the images based on the low-level features, high-level features, or the combination of both. Content-based image retrieval results can be improved by considering various features like directionality, contrast, coarseness, busyness, local binary pattern, and local tetra pattern with modified binary wavelet transform. In this research work, appropriate features are identified, applied and results are validated against existing systems. Modified binary wavelet transform is a modified form of binary wavelet transform and this methodology produced more similar retrieval images. The proposed system also combines the interactive feedback to retrieve the user expected results by addressing the issues of semantic gap. The quantitative evaluations such as average retrieval rate, false image acceptation ratio, and false image rejection ratio are evaluated to ensure the user expected results of the system. In addition to that, precision and recall are evaluated from the proposed system against the existing system results. When compared with the existing content-based image retrieval methods, the proposed approach provides better retrieval accuracy.

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Section: Interactive Rfmentioning

confidence: 99%

Section: Modified Binary Wavelet Transform–based Histogrammentioning

confidence: 99%