Double-Center-Based Iris Localization and Segmentation in Cooperative Environment with Visible Illumination

Li, Jiangang; Feng, Xin

doi:10.3390/s23042238

Cited by 4 publications

(3 citation statements)

References 32 publications

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“…The code used for double-membrane spacing analysis has been deposited to GitHub: github.com/GuoQLabPKU/Double-membrane_spacing ( 42 ). The RNA-seq data have been deposited to the BioSample Database ( https://www.ncbi.nlm.nih.gov/sra ) with the accession numbers SRR23974780 ( 43 ), SRR23974781 ( 44 ), SRR23974782 ( 45 ), and SRR23974783 ( 46 ).…”

Section: Data Materials and Software Availabilitymentioning

confidence: 99%

Vimentin regulates nuclear segmentation in neutrophils

Liu,

Li,

et al. 2023

Proc. Natl. Acad. Sci. U.S.A.

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Granulocytes are indispensable for various immune responses. Unlike other cell types in the body, the nuclei of granulocytes, particularly neutrophils, are heavily segmented into multiple lobes. Although this distinct morphological feature has long been observed, the underlying mechanism remains incompletely characterized. In this study, we utilize cryo-electron tomography to examine the nuclei of mouse neutrophils, revealing the cytoplasmic enrichment of intermediate filaments on the concave regions of the nuclear envelope. Aided by expression profiling and immuno-electron microscopy, we then elucidate that the intermediate-filament protein vimentin is responsible for such perinuclear structures. Of importance, exogenously expressed vimentin in nonimmune cells is sufficient to form cytoplasmic filaments wrapping on the concave nuclear surface. Moreover, genetic deletion of the protein causes a significant reduction of the number of nuclear lobes in neutrophils and eosinophils, mimicking the hematological condition of the Pelger–Huët anomaly. These results have uncovered a new component establishing the nuclear segmentation of granulocytes.

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Section: Data Materials and Software Availabilitymentioning

confidence: 99%

Vimentin regulates nuclear segmentation in neutrophils

Liu,

Li,

et al. 2023

Proc. Natl. Acad. Sci. U.S.A.

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“…Iris recognition has the advantages of uniqueness, stability, non-contact and anti-counterfeiting [1]~ [4] , and has a good development prospect in personal identity recognition [5] . Iris localization is an important part of iris recognition.…”

Section: Introductionmentioning

confidence: 99%

Robust iris localization algorithm based on improved YOLOv4 and self-organized particle swarm optimization

Li,

Tang

2024

Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023)

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Content Aiming at the problem that iris images are easily affected by eyelid and eyelash noise, which leads to low positioning accuracy and poor stability, an iris positioning network based on YOLOv4 model is proposed. Firstly, the backbone feature extraction network combining ECA attention mechanism and Densenet121 is introduced to enhance the feature extraction capability of the model. Secondly, the SPP module is improved and replaced with a deep detachable void space convolution pool pyramid to promote the information interaction between low-level location information and high-level semantic features. Finally, a self-organizing particle swarm optimization algorithm is designed to obtain the prior frame size that can characterize the overall features of iris data set. The proposed method was tested on the CIASIA-IrisV4 iris dataset, and the average accuracy of the improved model was 99.70%, and the positioning accuracy of the improved model was 95.89% in the case of light reflection generated by glasses. Compared with other iris positioning models, the accuracy and robustness were higher, which had obvious advantages.

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“…Despite exhibiting good robustness and resilience in iris localization, these methods suffered from a long computation time. With the rapid development of computer science and image processing technologies, iris localization methods based on computer vision and pattern recognition have constantly emerged, resulting in remarkable achievements [4].…”

Section: Introductionmentioning

confidence: 99%

An Application Study of Improved Iris Image Localization Based on an Evolutionary Algorithm

Niu,

Nie,

Liu

et al. 2023

Electronics

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This study aims to enhance the localization of the inner and outer circles of the iris while addressing issues of excessive invalid computations and inaccuracies. To achieve this objective, diverse methods are employed to improve the process to varying extents. Initially, the image undergoes pre-processing operations, including grayscale conversion, mathematical morphological transformation, noise reduction, and image enhancement. Subsequently, the accurate localization of the inner and outer edges is achieved by applying algorithms such as Canny edge detection and the Hough transform, allowing for the determination of their corresponding center and radius values within the iris image. Lastly, an improvement is made to the particle swarm optimization algorithm by combining various algorithms, namely LinWPSO, RandWPSO, contraction factor, LnCPSO, and AsyLnCPSO, employing mechanisms such as simulated annealing and the ant colony algorithm. Through dual validation on the CASIA-Iris-Syn dataset and a self-built CASIA dataset, this approach significantly enhances the precision of iris localization and reduces the required iteration count.

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Double-Center-Based Iris Localization and Segmentation in Cooperative Environment with Visible Illumination

Cited by 4 publications

References 32 publications

Vimentin regulates nuclear segmentation in neutrophils

Vimentin regulates nuclear segmentation in neutrophils

Robust iris localization algorithm based on improved YOLOv4 and self-organized particle swarm optimization

An Application Study of Improved Iris Image Localization Based on an Evolutionary Algorithm

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