An Efficient Fuzzy Based Edge Estimation for Iris Localization and Pupil Detection in Human Eye for Automated Cataract Detection System

Dixit, Aditya; Pathak, Shashwat; Raj, Rahul; Naveen, Ch.; Satpute, V. R.

doi:10.1109/icccnt.2018.8493740

Cited by 8 publications

(5 citation statements)

References 19 publications

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“…Different method of image processing techniques such as conservative smoothing, image de-noising, contrast enhancement and canny edge detection are implemented to enhance the quality of eye image and after it, described features were calculated to define a threshold between normal and diseased condition by mapping the opinion of doctor at training stage of threshold detection. 11 Pupil detection using developed approach [8] Edge detection in both vertical and horizontal region is performed to get total pixel count which corresponds to number of edges in b/w image for the purpose of cataract grading. Proposed method was found to be close to 98% accurate in detection of cataract.…”

Section: Discussionmentioning

confidence: 99%

“…Authors in [4, 7-9, 18, 23, 30] used several effective techniques based on use of different light sources, modelling and analysis of peculiar shapes, use of different transforms, enhanced Hough transform methods, analyzing mean gray levels for distinction between two circular regions and fuzzy based edge detection. Method using fuzzy based edge detection [8] has been developed and used in real-time detections in proposed system. Similarly, various cataract detection and grading methods are presented in Table 1 with their comparative limitations and system complexities to highlight the significance of proposed system.…”

Section: Literature Survey Of Image Processing Based Cataract Detecti...mentioning

confidence: 99%

“…Preprocessing, feature extraction, followed by decision making summarize the presented work. Image preprocessing includes conservative smoothing, image denoising, Gaussian filtering and edge detection using fuzzy based edge detector [8]. Preprocessing of digital eye is followed by contrast enhancement.…”

Section: Literature Survey Of Image Processing Based Cataract Detecti...mentioning

confidence: 99%

“…This fuzzy based algorithm was developed [17,28] and incorporated in the current system. A fuzzy approach was designed and tested for real-time [8], faithful edge estimation (Fig. 11.).…”

Section: ) Standard Deviation Values Further Adds Robustness To the C...mentioning

confidence: 99%

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Development of portable and robust cataract detection and grading system by analyzing multiple texture features for Tele-Ophthalmology

Pathak¹,

Raj

Singh³

et al. 2022

Multimed Tools Appl

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This paper presents a low cost, robust, portable and automated cataract detection system which can detect the presence of cataract from the colored digital eye images and grade their severity. Ophthalmologists detect cataract through visual screening using ophthalmoscope and slit lamps. Conventionally a patient has to visit an ophthalmologist for eye screening and treatment follows the course. Developing countries lack the proper health infrastructure and face huge scarcity of trained medical professionals as well as technicians. The condition is not very satisfactory with the rural and remote areas of developed nations. To bridge this barrier between the patient and the availability of resources, current work focuses on the development of portable low-cost, robust cataract screening and grading system. Similar works use fundus and retinal images which use costly imaging modules and image based detection algorithms which use much complex neural network models. Current work derives its benefit from the advancements in digital image processing techniques. A set of preprocessing has been done on the colored eye image and later texture information in form of mean intensity, uniformity, standard deviation and randomness has been calculated and mapped with the diagnostic opinion of doctor for cataract screening of over 200 patients. For different grades of cataract severity edge

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Section: Discussionmentioning

confidence: 99%

Section: Literature Survey Of Image Processing Based Cataract Detecti...mentioning

confidence: 99%

Section: Literature Survey Of Image Processing Based Cataract Detecti...mentioning

confidence: 99%

“…This fuzzy based algorithm was developed [17,28] and incorporated in the current system. A fuzzy approach was designed and tested for real-time [8], faithful edge estimation (Fig. 11.).…”

Section: ) Standard Deviation Values Further Adds Robustness To the C...mentioning

confidence: 99%

See 2 more Smart Citations

Development of portable and robust cataract detection and grading system by analyzing multiple texture features for Tele-Ophthalmology

Pathak¹,

Raj

Singh³

et al. 2022

Multimed Tools Appl

Self Cite

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“…Aditya Dixit et al [16] developed iris recognition approach based on fuzzy logic-based edge detection in the iris. A distinct approach is specified for iris localization and edge detection.…”

Section: Related Workmentioning

confidence: 99%

Enhanced Biometric Recognition for Secure Authentication Using Iris Preprocessing and Hyperelliptic Curve Cryptography

Rajasekar¹,

Premalatha²,

Sathya

2020

Wireless Communications and Mobile Computing

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Biometrics combined with cryptography can be employed to solve the conceptual and factual identity frauds in digital authentication. Biometric traits are proven to provide enhanced security for detecting crimes because of its interesting features such as accuracy, stability, and uniqueness. Although diverse techniques have been raised to address this objective, limitations such as higher computational time, minimal accuracy, and maximum recognition time remain. To overcome these challenges, an enhanced iris recognition approach has been proposed based on hyperelliptic curve cryptography (HECC). The proposed study uses the 2D Gabor filter approach for perfect feature extraction in iris preprocessing. A lightweight cryptographic scheme called HECC was employed to encrypt the iris template to avoid intentional attack by the intruders. The benchmark CASIA Iris V-4 and IITD iris datasets were used in the proposed approach for experimental analysis. The result analysis witnessed that the prime objective of the research such as lesser false acceptance rate, lesser false rejection rate, maximum accuracy of 99.74%, maximum true acceptance rate of 100%, and minimal recognition time of 3 seconds has been achieved. Also, it has been identified that the proposed study outperforms other existing well-known techniques.

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Fuzzy Logic-Based Software Systems

Chrysafiadi

2023

Learning and Analytics in Intelligent Systems

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An Efficient Fuzzy Based Edge Estimation for Iris Localization and Pupil Detection in Human Eye for Automated Cataract Detection System

Cited by 8 publications

References 19 publications

Development of portable and robust cataract detection and grading system by analyzing multiple texture features for Tele-Ophthalmology

Development of portable and robust cataract detection and grading system by analyzing multiple texture features for Tele-Ophthalmology

Enhanced Biometric Recognition for Secure Authentication Using Iris Preprocessing and Hyperelliptic Curve Cryptography

Fuzzy Logic-Based Software Systems

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