Center-symmetric local binary pattern based on weighted neighbor contribution

Hu, Pei; Shao, Yi; Tang, Chaowei; Siman, Zhao

doi:10.1016/j.ijleo.2016.09.040

Optik

2016

DOI: 10.1016/j.ijleo.2016.09.040

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Center-symmetric local binary pattern based on weighted neighbor contribution

Pei Hu

Yi Shao

Chaowei Tang

et al.

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Cited by 3 publications

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“…Previous methods based on radial information[41,42] report improved stability of features at different resolutions, more efficient computations, and robustness to noise; these are some of the motivations to extend radial-based descriptors to applications in cell analysis, as described in the next section.…”

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confidence: 99%

Radial feature descriptors for cell classification and recommendation

Silva

Araújo

Ushizima

et al. 2019

Journal of Visual Communication and Image Representation

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This paper introduces computational tools for cell classification into normal and abnormal, as well as content-based-image-retrieval (CBIR) for cell recommendation. It also proposes the radial feature descriptors (RFD), which define evenly interspaced segments around the nucleus, and proportional to the convexity of the nuclear boundary. Experiments consider Herlev and CRIC image databases as input to classification via Random Forest and bootstrap; we compare 14 different feature sets by means of False Negative Rate (FNR) and Kappa (κ), obtaining FNR= 0.02 and κ = 0.89 for Herlev, and FNR= 0.14 and κ = 0.78 for CRIC. Next, we sort and rank cell images using convolutional neural networks and evaluate performance with the Mean Average Precision (MAP), achieving MAP= 0.84 and MAP= 0.82 for Herlev and CRIC, respectively. Cell classification show encouraging results regarding RFD, including its sensitivity to intensity variation around the nuclear membrane as it bypasses cytoplasm segmentation.

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confidence: 99%

Radial feature descriptors for cell classification and recommendation

Silva

Araújo

Ushizima

et al. 2019

Journal of Visual Communication and Image Representation

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Computer Vision-Based Severity Classification of Asphalt Pavement Raveling Using Advanced Gradient Boosting Machines and Lightweight Texture Descriptors

Hoang

Tran

2023

Iran J Sci Technol Trans Civ Eng

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A novel and accurate chess pattern for automated texture classification

Tuncer

Doğan

Ataman

2019

Physica A: Statistical Mechanics and its Applications

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Center-symmetric local binary pattern based on weighted neighbor contribution

Cited by 3 publications

References 11 publications

Radial feature descriptors for cell classification and recommendation

Radial feature descriptors for cell classification and recommendation

Computer Vision-Based Severity Classification of Asphalt Pavement Raveling Using Advanced Gradient Boosting Machines and Lightweight Texture Descriptors

A novel and accurate chess pattern for automated texture classification

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