Enhanced Binary Hexagonal Extrema Pattern (EBHXEP) Descriptor for Iris Liveness Detection

The Word Sense Disambiguation system (WSD) is widely used in many fields, including business, research, education, and government organizations. The availability of natural language data on the internet has grown in tandem with the rapid advancement of technology and the widespread use of the internet. Disambiguation is best tool for avoiding the problem of misperception. The most important feature of this approach is that words with multiple meanings of nouns can be easily disambiguated according to the sense of the sentences. As a result of incorporating all of these factors, This work will concentrate on the accuracy of adjectives and verbs. Many natural languages, including English, German, Arabic, Assamese, and others, have different methodologies proposed, however, work on Word Sense Disambiguation in Hindi is limited. For Hindi Word Sense Disambiguation, the proposed algorithm employs a genetic algorithm. The dynamic configuration window function, including the ambiguous terms left and right, is used. The central tenet of this method is that the target term and its surroundings share a common topic. With approximately 65.17%, 72%, and 74.1 %, respectively, the proposed work has compared to existing approaches such as graph-based approaches, association rules approaches, and probabilistic latent semantic analysis approaches. The proposed method has an accuracy of 80%, which indicating that it improves the existing Work by 8% in terms of accuracy and other parameters. Results show that the proposed work generates more accurate results for Hindi word sense disambiguation.

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“…The experiment was conducted for manually created sense inventories for about 60 polysemous nouns. The maximum precision achieved is 54.54% [19].…”

Section: Literature Surveymentioning

confidence: 92%

Role of Genetic Algorithm in Optimization of Hindi Word Sense Disambiguation

2022

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“…Through careful manipulation of image, the solution can be deceived. Agarwal et al [18] proposed a local descriptor for detecting iris spoofing. The descriptor is productive and learns correlation for a pixel with its hexagonal neighbors.…”

Section: Related Workmentioning

confidence: 99%

“…Higher error due to surrounding artificial light sources Chou et al [15] Challenge response in terms of audio feedback Can be deceived easily Boutellaa et al [16] Voice modality based challenge response Can be deceived using voice faking Wang et al [17] Analyzed depth information from image captured using two cameras Can be deceived with careful manipulation of image Agarwal et al [18] local descriptor for detecting iris spoofing. Fails for video replay attacks Bhogal et al [19] six different picture quality measures to assess genuine biometric attributes easy to create masks to deceive these quality measures Fathy et al [20] Thresholded entropy esteems to detect iris spoofing Fails in case of illuminations Nguyen et al [21] Multi modal acquiring iris acquisition with varying light intensities.…”

Section: A Liveliness Detectionmentioning

confidence: 99%

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Challenge Responsive Multi Modal Biometric Authentication Resilient to Presentation Attacks

2022

IJIES

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Multimodal biometric systems are a natural evolution of traditional biometric authentication systems with use of multiple biometric to enhance the security level. Presentation attacks in form of photos and replay videos are becoming a threat to the biometric authentication systems and it becomes necessary to prevent from these attacks for an enhanced security level. This work proposes a challenge response based multi modal biometric authentication resilient to presentation attack. The proposed system is designed for multi modal biometric involving face and iris biometrics with challenge in form of arbitrary emotion invoking image at a random position on the screen. The changes in region of interest around the Facial landmarks and distance of iris to Facial landmarks are captured as response. The response is then matched with expected response derived based on the position of arbitrary emotion invoking image on screen to detect presentation attacks. In addition the work also proposes a hybrid deep feature which provides an addition security in recognition process to ensure authentication failure for fake samples. The error rate in leakage of spoofs is very low in proposed solution (less than 1%) in different environments compared to existing works. The recognition accuracy of face is atleast 1% higher and atleast 2% higher for IRIS in proposed solution compared to existing works.

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“…It is a subset of digital imaging. This versatile technique [2] can process both visual images and analog images. Agarwal et al demonstrated various prominent imaging techniques, and explained how they have been used in practice.…”

Section: Introductionmentioning

confidence: 99%

Detection of Copy-Move Forgery Using Euclidean Distance and Texture Features

Kumar¹,

Singh²,

Swarup³

et al. 2022

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Given the pivotal role of digital images in our daily lives, it is important to detect copy-move forgery (CMF) of digital images. The detection of CMF is often based on feature detection and matching. For feature matching, the existing algorithms make use of the Euclidean distance. For feature detection, the Haar transform is one of the most popular techniques. This study retrieves image features through the Haar transform, and then simplifies the features by principal component analysis (PCA). After that, false boundaries were detected, localized, and removed. On this basis, the texture features of the input image were analyzed, using the gray-level co-occurrence matrix (GLCM). Finally, Euclidean distance was utilized to match features, and the mismatched features were labeled as forgeries. Then, the proposed approach was simulated in MATLAB, with accuracy as the performance metric. The simulation results show that our approach outperformed the PCA by 13.6% in accuracy.

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Enhanced Binary Hexagonal Extrema Pattern (EBHXEP) Descriptor for Iris Liveness Detection

Cited by 22 publications

References 26 publications

Role of Genetic Algorithm in Optimization of Hindi Word Sense Disambiguation

Role of Genetic Algorithm in Optimization of Hindi Word Sense Disambiguation

Challenge Responsive Multi Modal Biometric Authentication Resilient to Presentation Attacks

Detection of Copy-Move Forgery Using Euclidean Distance and Texture Features

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