RANSAC lens boundary feature based kernel SVM for transparent contact lens detection

Kumar, Mohit; Puhan, Niladri B.

doi:10.1049/iet-bmt.2017.0161

Cited by 8 publications

(3 citation statements)

References 37 publications

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“…The gradient orientation of the boundary was extracted using a gradient histogram. On the other hand, previous study [32] presented a new transparent contact lens detection method for classifying an eye image into no lens or transparent lens categories. In order to extract significant edge points in the sclera ROI, the input image was first segmented.…”

Section: Image Processing Approachmentioning

confidence: 99%

A review on contact lens inspection

Mana

Chin

Fook³

et al. 2023

IJEECS

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<span><span lang="EN-US">Over the year, contact lens detection has attracted attention and interest from many researchers to study further in this field of inspection. This paper provides a comprehensive review of the existing literature surrounding contact lens inspection methods. In this paper, contact lens-related, defects-related, and inspection methods related are described in detail. To detect contact lenses in a single image and also multi-image, numerous techniques have been developed and this paper is aimed at classifying and evaluating these algorithms. Also, contact lens inspection based on conventional and artificial intelligence methods will be discussed in detail. The industrial production process of contact lenses probably needs to be constructed with advanced tools based on recent technologies so that they can help in the inspection system to achieve accurate results of the inspection and reduce processing time</span>. </span>

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Section: Image Processing Approachmentioning

confidence: 99%

A review on contact lens inspection

Mana

Chin

Fook³

et al. 2023

IJEECS

View full text Add to dashboard Cite

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“…In [23], a new Circlet Transform (CTT) is implemented for the analysis of microscopic images, detecting and counting red blood cells, achieving an accuracy of 93.3 %. On the other hand, the Random Sample Consensus (RANSAC) algorithm is proposed for the circular detection of transparent contact lenses using an SVM image classifier [24], achieving an accuracy of 90.63 %. In the same way, in [25], the same algorithm is used for the automatic gauge detection to find the most fitted ellipse to the targeted object.…”

Section: A Related Workmentioning

confidence: 99%

Bullet Impact Detection in Silhouettes Using Mask R-CNN

Vilchez

Mauricio

2020

IEEE Access

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The bullet impact detection in the silhouette plays an important role in the institutions which have a shooting range, specially where are regulated the license to carry a gun and where the evaluation manual process could present distortion in the ability's evaluation of the shooter and like a consequence the license's issuance. This paper proposes a method for an automatic detection of the bullet impacts in silhouettes based on deep learning and image processing, which consist of the following steps: preprocessing, impacts detection, edge detection and evaluation results. The experiments about 600 silhouettes with 2401 bullet impacts images of the proposed and implemented method considering the models Resnet 50 and Resnet 101 for Mask R-CNN show that Resnet 50 get better results than Resnet 101, achieving 97.6 %, 99.5 %, and 97.9 %, of accuracy, precision and recall, respectively, above the methods Circular Hough Transform, Circlet Detection, Random Sample Consensus, Randomized Hough Transform, Randomized Circle Detection, Support Vector Machine, Faster R-CNN, MnasNet and YOLO. Also, the results show 100 % of effectiveness in the edge detection and the count of the detected bullet impacts.INDEX TERMS Edge detection, bullet impact detection, image processing, Mask R-CNN.

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“…Compared with the LS method, RANSAC is more robust, but its detection accuracy is limited by the iterative times. When the iterative time is unreasonable, the errors of ellipse parameters are very large [13][14][15]. The last category is Hough transform (HT).…”

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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RANSAC lens boundary feature based kernel SVM for transparent contact lens detection

Cited by 8 publications

References 37 publications

A review on contact lens inspection

A review on contact lens inspection

Bullet Impact Detection in Silhouettes Using Mask R-CNN

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

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