2021
DOI: 10.3390/math9212790
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Abstract: At present, iris recognition has been widely used as a biometrics-based security enhancement technology. However, in some application scenarios where a long-distance camera is used, due to the limitations of equipment and environment, the collected iris images cannot achieve the ideal image quality for recognition. To solve this problem, we proposed a modified sparrow search algorithm (SSA) called chaotic pareto sparrow search algorithm (CPSSA) in this paper. First, fractional-order chaos is introduced to enha… Show more

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Cited by 18 publications
(5 citation statements)
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“…Xiong et al [ 74 ] introduced another chaotic SSA for enhancement of long-distance iris image, called CPSSA. First, fractional-order chaos was utilized for generating the initial population to enhance the population diversity.…”
Section: Recent Variants Of Ssamentioning
confidence: 99%
See 1 more Smart Citation
“…Xiong et al [ 74 ] introduced another chaotic SSA for enhancement of long-distance iris image, called CPSSA. First, fractional-order chaos was utilized for generating the initial population to enhance the population diversity.…”
Section: Recent Variants Of Ssamentioning
confidence: 99%
“…The SSA is also used to assess the BP neural networks to address the imaging deviation prediction [ 114 ]. The long-distance iris image is enhanced using a chaotic version of SSA [ 74 ]. Finally, the Camera calibration is optimized using the original version of SSA [ 86 ].…”
Section: Applications Of Ssamentioning
confidence: 99%
“…To avoid the local minimum points, the Pareto distribution is utilized [25]. As a result, the scroungers' location update formula is changed by Eq.…”
Section: Updating Scroungers' Locationsmentioning
confidence: 99%
“…Table 2 contains the best value, average, standard deviation, and computation time. The best value reflects exploration ability, the average value demonstrates convergence accuracy, and the standard deviation depicts the SPSSA's stability under the same benchmark test function [25].…”
Section: Benchmark Function Comparison Experimentsmentioning
confidence: 99%
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