ROI image retrieval based on multiple features of mean shift and expectation–maximisation

Chen, Wenbing; Li, Qizhou; Dahal, Keshav

doi:10.1016/j.dsp.2015.01.003

Cited by 2 publications

(2 citation statements)

References 40 publications

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“…A combination of the mean shift tracking (MST) and an improved expectation-maximization (EM)like (IEML) methods have been used by Chen et al (2015) to produce a novel ROI image retrieval. MST functions to seek the initial location of the target candidate model meanwhile IEML is used to adaptively change the location and scale of the target candidate model.…”

Section: Related Workmentioning

confidence: 99%

Region-based image retrieval using region of interest (ROI) according to incremental frame and clustering color image

al.¹

2022

Int. j. adv. appl. sci.

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Content-based image retrieval involves the extraction of global feature images for their retrieval performance in large image databases. Extraction of global features image cause problem of the semantic gap between the high-level meaning and low-level visual features images. In this study RBIR, Region of Interest Based (ROI) Image Retrieval Using Incremental Frame of Color Image was proposed. It combines several methods, including filtering process, image partitioning using clustering and incremental frame formation, complementation law of theory set to generate ROI, NROI, or ER of the region. The concept of weighting as well as a significant query is also incorporated as a query strategy. Extensive experiments were also conducted on the Wang database and the color model selected was the CIE lab. Experimental results show the proposed method is efficient in image retrieval. The performance of the proposed method shows a better average IPR value of 3.51% compared to RGB and 22.92% with the HSV color model. Meanwhile, it also performs better by 36%, 5%, and 24% compared to methods CH (8,2,2), CH (8,3,3), and CH (16,4,4).

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Section: Related Workmentioning

confidence: 99%

Region-based image retrieval using region of interest (ROI) according to incremental frame and clustering color image

al.¹

2022

Int. j. adv. appl. sci.

View full text Add to dashboard Cite

show abstract

“…Duong et al [40] developed a nearest neighbor estimator of the order derivatives of the probability density function using mean shift clustering. Consequently, Chen et al [41]…”

Section: Introductionmentioning

confidence: 99%