2019
DOI: 10.3390/jimaging5030033
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Abstract: Digitalisation has opened a wealth of new data opportunities by revolutionizing how images are captured. Although the cost of data generation is no longer a major concern, the data management and processing have become a bottleneck. Any successful visual trait system requires automated data structuring and a data retrieval model to manage, search, and retrieve unstructured and complex image data. This paper investigates a highly scalable and computationally efficient image retrieval system for real-time conten… Show more

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Cited by 20 publications
(4 citation statements)
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References 68 publications
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“…Texture function describes variations between pixel intensities in spatial relations. A number of studies have applied texture feature for video and image retrieval [1], [21]- [27]. Many researchers have employed LBP-based texture feature for image or vide retrieval because of its robustness for scale and rotation [1].Though, many researchers have applied the LBP-based textures, they have computed the LBP by simply subtract the neighboring pixel intensity values from its center pixel of a sub image.…”
Section: Texture Featuresmentioning
confidence: 99%
“…Texture function describes variations between pixel intensities in spatial relations. A number of studies have applied texture feature for video and image retrieval [1], [21]- [27]. Many researchers have employed LBP-based texture feature for image or vide retrieval because of its robustness for scale and rotation [1].Though, many researchers have applied the LBP-based textures, they have computed the LBP by simply subtract the neighboring pixel intensity values from its center pixel of a sub image.…”
Section: Texture Featuresmentioning
confidence: 99%
“…A deep CNN model is utilized in [7] to extract the feature representation from the activations of the convolutional layers in a large image dataset for applications such as remote sensing and plant biology. Then database indexing structure and recursive density estimation are established to retrieve the images in a fast and efficient way.…”
Section: Reletated Workmentioning
confidence: 99%
“…Pouria Sadeghi et al [20] offers an exceptionally scalable and computationally efficient image retrieval system for real-time content-based searching through large-scale image repositories within the domain of remote sensing and plant biology. Convolutional Neural Network is used as a function extractor to derive deep characteristic representations from the imaging data.…”
Section: Machine Learning Paradigm Towards Content Based Image Retriementioning
confidence: 99%