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Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images by Jamaludin, Shahrizan, Mohamad Ayob, Ahmad Faisal, Mohd Norzeli, Syamimi, Mohamed, Saiful Bahri

“…Moreover, evolution or convergence speed remains a significant challenge for active contour as it segments the precise iris boundary. …”
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Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso by Mohammed Adam Kunna, Azrag, Jasni Mohamad, Zain, Tuty Asmawaty, Abdul Kadir, Marina, Yusoff, Jaber, Aqeel Sakhy, Abdlrhman, Hybat Salih Mohamed, Ahmed, Yasmeen Hafiz Zaki, Husain, Mohamed Saad Bala

“…In this regard, the result of the ESe-PSO algorithm achieved superior accuracy compared with the Segment Particle Swarm Optimization (Se-PSO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE) algorithms. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…Among others, multilevel thresholding is a robust and most widely adopted image segmentation approach. To find the optimal multilevel threshold values, various heuristic and meta-heuristic algorithms have been applied to segment COVID-19 medical images. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…Among others, multilevel thresholding is a robust and most widely adopted image segmentation approach. To find the optimal multilevel threshold values, various heuristic and meta-heuristic algorithms have been applied to segment COVID-19 medical images. …”
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Segmentation of Retinal Vasculature using Active Contour Models (Snakes) by Pang, Kee Y ong

“…Active contour model (snake) that based on level sets, techniques of curve evolution, and Mumford-Shah functional for segmentation is then used to segment out the detected retinal vessel and produce a complete retinal vasculature. …”
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Vibrant search mechanism for numerical optimization functions by Shambour, Moh’d Khaled Yousef

“…In this paper, a novel heuristic technique is introduced to enhance the search capabilities of an algorithm, focusing on certain search spaces during evolution process. …”
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Iris Segmentation Analysis using Integro-Differential Operator and Hough Transform in Biometric System by Zainal Abidin, Zaheera, -, M.Manaf, Shibghatullah, Abdul Samad, -, S.H.A.Mohd Yunos, -, S.Anawar, -, Z.Ayop

“…Iris segmentation is foremost part of iris recognition system. …”
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Iris Segmentation Analysis Using Integro-Differential Operator And Hough Transform In Biometric System by Zainal Abidin, Zaheera, Anawar, Syarulnaziah, Ayop, Zakiah, Manaf, Mazani, Shibghatullah, A.S., Mohd Yunos, S.H.A.

“…Iris segmentation is foremost part of iris recognition system.There are four steps in iris recognition: segmentation,normalization,encoding and matching.Here, iris segmentation has been implemented using Hough Transform and IntegroDifferential Operator techniques.The performance of iris recognition system depends on segmentation and normalization technique.Iris recognition systems capture an image from individual eye.Then the image captured is segmented and normalized for encoding process.The matching technique,Hamming Distance,is used to match the iris codes of iris in the database weather it is same with the newly enrolled for verification stage.These processes produce values of average circle pupil,average circle iris,error rate and edge points.The values provide acceptable measures of accuracy False Accept Rate (FAR) or False Reject Rate (FRR).Hough Transform algorithm,provide better performance,at the expense of higher computational complexity.It is used to evolve a contour that can fit to a non-circular iris boundary.However,edge information is required to control the evolution and stopping the contour.The performance of Hough Transform for CASIA database was 80.88% due to the lack of edge information.The GAR value using Hough Transform is 98.9% genuine while 98.6% through Integro-Differential Operator.…”
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Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach by Avazpour, Iman, Roslan, Ros Ernida, Bayat, Peyman, Saripan, M. Iqbal, Nordin, Abdul Jalil, Raja Abdullah, Raja Syamsul Azmir

“…The results show that the mean standard error for over segmented pixels is 33% while for the under segmented pixels is 3.4%. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images by Singh, V., Elamvazuthi, I., Jeoti, V., George, J., Swain, A., Kumar, D.

“…The enhanced contrast image is further optimized by the particle swarm optimization algorithm. Thereafter, the optimized image is processed by the Chan-Vese method to extract the ATFL region through curve evolution; then the resultant image smoothed by morphological operation. …”
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Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images by Singh, V., Elamvazuthi, I., Jeoti, V., George, J., Swain, A., Kumar, D.

“…The enhanced contrast image is further optimized by the particle swarm optimization algorithm. Thereafter, the optimized image is processed by the Chan-Vese method to extract the ATFL region through curve evolution; then the resultant image smoothed by morphological operation. …”
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Enhanced image segmentation in thermal infrared image processing for faulty detection on broadcasting equipment / Mohd Rizman Sultan Mohd, Sukreen Hana Herman and Zaiton Sharif by Mohd, Mohd Rizman Sultan, Herman, Sukreen Hana, Sharif, Zaiton

“…The data gathered from the system will undergo enhanced image segmentation method using k-means clustering with the implementation of histogram equalization for further image processing algorithm to detect the presence of hot spot. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush