Intelligent Hough Transform With Jaya to Detect the Diameter of Red-Hot Circular Workpiece

Zhang, Xinyu; Mu, Rong; Chen, Ke; Yang, Yanxi; Chen, Yajun

doi:10.1109/jsen.2020.3015134

Cited by 15 publications

(11 citation statements)

References 27 publications

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“…Also, two doctors performed the segmentation procedure manually to inaugurate the ground truth. From the table, the proposed procedure achieved 0.87 Dice, while the circular Hough transform achieved lower Dice index of 0.5633, Chanvese has a Dice index of 0.5376, the Daugman procedures [25] achieves better dice similarity but lower than the proposed method the Daugman procedures achieved 0.7616. The manual segmentation by the two doctors is in agreement with the result of our proposed method.…”

Section: Corneal Segmentationmentioning

confidence: 91%

“…It utilizes chrominance components of reduced bandwidth. The normalized RGB masks errors and compression artifacts in a more efficient way than RGB encoding direct scheme [23][24][25][26][27]. The second step is the edge enhancement step because it is very crucial for image enhancement for the purpose of medical image analysis and recognition.…”

Section: The Preprocessing Phasementioning

confidence: 99%

“…The four methods are our proposed method, the circular Hough transform [23,24], Chanvese and the Daugman procedures. The comparison utilizes the Dice similarity index [25][26][27]. Also, two doctors performed the segmentation procedure manually to inaugurate the ground truth.…”

Section: Corneal Segmentationmentioning

confidence: 99%

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Computerized Detection of Limbal Stem Cell Deficiency from Digital Cornea Images

Mahmoud¹,

Khafga²,

Alharbi³

2022

Computer Systems Science and Engineering

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Limbal Stem Cell Deficiency (LSCD) is an eye disease that can cause corneal opacity and vascularization. In its advanced stage it can lead to a degree of visual impairment. It involves the changing in the semispherical shape of the cornea to a drooping shape to downwards direction. LSCD is hard to be diagnosed at early stages. The color and texture of the cornea surface can provide significant information about the cornea affected by LSCD. Parameters such as shape and texture are very crucial to differentiate normal from LSCD cornea. Although several medical approaches exist, most of them requires complicated procedure and medical devices. Therefore, in this paper, we pursued the development of a LSCD detection technique (LDT) utilizing image processing methods. Early diagnosis of LSCD is very crucial for physicians to arrange for effective treatment. In the proposed technique, we developed a method for LSCD detection utilizing frontal eye images. A dataset of 280 eye images of frontal and lateral LSCD and normal patients were used in this research. First, the cornea region of both frontal and lateral images is segmented, and the geometric features are extracted through the automated active contour model and the spline curve. While the texture features are extracted using the feature selection algorithm. The experimental results exhibited that the combined features of the geometric and texture will exhibit accuracy of 95.95%, sensitivity of 97.91% and specificity of 94.05% with the random forest classifier of n = 40. As a result, this research developed a Limbal stem cell deficiency detection system utilizing features' fusion using image processing techniques for frontal and lateral digital images of the eyes.

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Section: Corneal Segmentationmentioning

confidence: 91%

Section: The Preprocessing Phasementioning

confidence: 99%

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Computerized Detection of Limbal Stem Cell Deficiency from Digital Cornea Images

Mahmoud¹,

Khafga²,

Alharbi³

2022

Computer Systems Science and Engineering

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“…Especially, it gets worse in ellipse fitting because there are four parameters in an elliptic equation at least. To address this issue, the IHTJ is proposed in [28]. This method maps (1) into the parameter space and designs a fitness function firstly, and then, it transforms the ellipse fitting to seek the optimum value in the parametric space, which can get the peak value of the HT's accumulator.…”

Section: Ihtj Reviewmentioning

confidence: 99%

“…With the development of artificial intelligence (AI) methods, some AI methods have been introduced in signal processing [25][26][27]. Recently, Zhang et al propose an intelligent HT with Jaya (IHTJ) in [28], which transforms the ellipse fitting into an optimal problem, thus using Jaya to seek the optimum solution in the parameter space. The speed and accuracy of the HT are improved greatly.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Hough Transform with Jaya of Multipopulation Cooperation for Diameter Estimation of Red-Hot Workpiece

Zhang

Chen

et al. 2022

Wireless Communications and Mobile Computing

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Diameter is a critical metric during producing circular workpieces, but it is always challenging to measure accurately due to the existence of noise. The intelligent Hough transform with Jaya (IHTJ) is developed to solve this issue recently. However, it suffers from some disadvantages including unsatisfactory accuracy and convergence rate caused by the problem of trapping into local optimization in the case of inaccurate priori knowledge. In this paper, an IHTJ of multipopulation cooperation (IHTJMC) is proposed to overcome these disadvantages. Firstly, we analyse the problem of IHTJ in the diameter measurement. Secondly, a ring structure of the multipopulation cooperation is designed. In this structure, the whole population is divided into several subpopulations which evolve independently all the time. This can ensure a few best and worst solutions guide the evolution of the whole population at the same time. Then, we propose a migration strategy to finish the cooperation among the different subpopulations, which selects a few individuals from each subpopulation randomly, and exchange them with each other. This strategy can make the different subpopulations share the information among the entire population and improve the global search ability. Finally, three experiments are introduced to test the effectiveness of the IHTJMC. The experimental results demonstrate that the IHTJMC can restrain the problem of falling into local optimization significantly. Compared with the existing methods, it has superior accuracy and robustness for the diameter measurement of a circular workpiece which is heated to red state.

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Elimination of parasitic interference effect in fiber-optic external sinusoidal phase-modulating interferometer based on Kalman filter

et al. 2022

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Intelligent Hough Transform With Jaya to Detect the Diameter of Red-Hot Circular Workpiece

Cited by 15 publications

References 27 publications

Computerized Detection of Limbal Stem Cell Deficiency from Digital Cornea Images

Computerized Detection of Limbal Stem Cell Deficiency from Digital Cornea Images

An Intelligent Hough Transform with Jaya of Multipopulation Cooperation for Diameter Estimation of Red-Hot Workpiece

Elimination of parasitic interference effect in fiber-optic external sinusoidal phase-modulating interferometer based on Kalman filter

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