Combined global-local specialized feature descriptor for content based image retrieval under noisy query

Singaravelan, S.; Murugan, D.

doi:10.1109/icaccs.2013.6938716

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Cited by 3 publications

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“…2) Gaussian noise is statistical noise which has its probability density function equals to normal distribution also known as the Gaussian distribution. The special case of Gaussian noise is white noise in which values at any pair are statistically independent and identically distributed [10].…”

Section: Effect Of Noisementioning

confidence: 99%

Content based Image Retrieval using Median Binary Pattern with Structure Element Descriptor on Noisy Images

Desai¹

2019

IJRASET

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Effective features are essential issue for the representation and recognition of images. In this paper, we present a new feature representation method for image retrieval based on Median Binary Pattern (MBP) and Structure Element Descriptor, named Median Binary Pattern extended structure element descriptor (MBP-SED). Firstly, the gray scale image is converted using the MBP. The elements in the structure can effectively represent the bitmap which is generated by MBP. Global Feature is achieved using the combination of MBP-SED and color Histogram (CH). Proposed system is more reliable on noisy images. Experiments on Corel-1k dataset show that MBP-SED outperforms than other descriptors.

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Section: Effect Of Noisementioning

confidence: 99%