TY - CPAPER
KW - Color
KW - Color image processing
KW - Colour image
KW - Colour image segmentation
KW - Image enhancement
KW - Image segmentation
KW - Kapur entropy
KW - Kapur s entropy
KW - Levy flight
KW - Levy flights
KW - Muli-threshold color image segmentation
KW - Multilevel thresholding
KW - Optimization
KW - Optimization algorithms
KW - Renyi entropy
KW - Renyi s entropy
KW - Signal to noise ratio
KW - Thresholding segmentation
KW - Whale optimization algorithm
AU - X.-W. Cheng
AU - H.-Q. Wang
AU - G.-C. Chen
AB - The whale optimization algorithm has the shortcomings of precocity and insufficient diversity when it is used to segment the color lantern image. A chaotic levy whale optimization algorithm is proposed to search the optimal Kapur s entropy and Renyi entropy. In this algorithm, particles are used to represent a feasible one-dimensional multi threshold vector, and chaos initialization strategy is adopted to improve the randomness of the algorithm. Based on the whale optimization algorithm, Levy flight strategy is used to enhance the diversity and global search ability of the algorithm. The simulation results show that the proposed algorithm is better than the other five algorithms. In addition, the algorithm using Renyi entropy has better performance than Kapur s entropy in terms of Signal to Noise Ratio (PSNR), Feature Similarity index (FSIM), and best fitness. It also provides a reference for the application of swarm intelligence algorithm in intangible cultural heritage image segmentation.
C2 - Int. Conf. Pattern Recognit. Artif. Intell., PRAI
DO - 10.1109/PRAI53619.2021.9551031
LA - English
N1 - Journal Abbreviation: Int. Conf. Pattern Recognit. Artif. Intell., PRAI
N2 - The whale optimization algorithm has the shortcomings of precocity and insufficient diversity when it is used to segment the color lantern image. A chaotic levy whale optimization algorithm is proposed to search the optimal Kapur s entropy and Renyi entropy. In this algorithm, particles are used to represent a feasible one-dimensional multi threshold vector, and chaos initialization strategy is adopted to improve the randomness of the algorithm. Based on the whale optimization algorithm, Levy flight strategy is used to enhance the diversity and global search ability of the algorithm. The simulation results show that the proposed algorithm is better than the other five algorithms. In addition, the algorithm using Renyi entropy has better performance than Kapur s entropy in terms of Signal to Noise Ratio (PSNR), Feature Similarity index (FSIM), and best fitness. It also provides a reference for the application of swarm intelligence algorithm in intangible cultural heritage image segmentation.
PB - Institute of Electrical and Electronics Engineers Inc.
PY - 2021
SN - 9781665413220 (ISBN)
SP - 28
EP - 34
TI - An improved whale optimization algorithm for dinosaur lantern festival color image multilevel thresholding segmentation
UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117961924&doi=10.1109%2fPRAI53619.2021.9551031&partnerID=40&md5=6d31e76559a3c59c161ae86b8397dcf6
ER -