• Advances in environmental research
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• v.12 no.2
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• pp.113-122
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• 2023

Biometric authentication has become an essential part of modern-day security systems, especially in financial institutions like banks. A face recognition-based ATM is a biometric authentication system, that uses facial recognition technology to verify the identity of bank account holders during ATM transactions. This technology offers a secure and convenient alternative to traditional ATM transactions that rely on PIN numbers for verification. The proposed system captures users' pictures and compares it with the stored image in the bank's database to authenticate the transaction. The technology also offers additional benefits such as reducing the risk of fraud and theft, as well as speeding up the transaction process. However, privacy and data security concerns remain, and it is important for the banking sector to instrument solid security actions to protect customers' personal information. The proposed system consists of two stages: the first stage captures the user's facial image using a camera and performs pre-processing, including face detection and alignment. In the second stage, machine learning algorithms compare the pre-processed image with the stored image in the database. The results demonstrate the feasibility and effectiveness of using face recognition for ATM authentication, which can enhance the security of ATMs and reduce the risk of fraud.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.309-316
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• 2024

Facial recognition technology is widely used in various fields but faces challenges due to its vulnerability to fraudulent activities such as photo spoofing. Extensive research has been conducted to overcome this challenge. Most of them, however, require the use of specialized equipment like multi-modal cameras or operation in high-performance environments. In this paper, we introduce LH-FAS v2 (: Lightweight Head-pose-based Face Anti-Spoofing v2), a system designed to operate on a commercial webcam without any specialized equipment, to address the issue of facial recognition spoofing. LH-FAS v2 utilizes FSA-Net for head pose estimation and ArcFace for facial recognition, effectively assessing changes in head pose and verifying facial identity. We developed the VD4PS dataset, incorporating photo spoofing scenarios to evaluate the model's performance. The experimental results show the model's balanced accuracy and speed, indicating that head pose estimation-based facial anti-spoofing technology can be effectively used to counteract photo spoofing.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.114-116
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• 2004

Biometrics consist of technologies that support automatic identification or verification of identity based on behavioral or physical traits. Biometrics can authenticate identities since they measure unique individual characteristics including fingerprints, hand geometry, iris, hand vascular patterns and facial characteristics. we review the state of the hand vascular patterns identification technology and compare other competitive authentication technologies such as cryptography, electronic signature and PKI.

• Journal of Broadcast Engineering
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• v.11 no.1 s.30
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• pp.15-27
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• 2006

In this paper, a novel approach is addressed to facilitate the browsing of large collection of digital photos associated with specified person(s) in the photos. The goal of the proposed method is to exploit additional person-identity features as incorporating facial regions and peripheral clothes region associated with them. For more effective incorporation of the clothes and facial features, situation-based photo clustering is also proposed. To evaluate the efficacy of the proposed method experiment was performed with 1120 generic home photos. The experiment results showed that the proposed method outperformed the conventional method us El.g only face feature as showing the average performance of about 92% contrary to the average performance of about 70% in the conventional method.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1139-1148
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• 2003

Biometric system has been studied as an optimal solution for preventing or reducing the peculation or loss of ID. Nowadays, face recognition has been spot-lighted as a future biometric system because it is not forced to contact the part of human body with the specific input area of the system. However, there is some limitations to get the constant facial features because the size of face area is varied by the capturing distance or tilt of the face. In this paper, we can extract constant facial features within the predefined threshold using the simple geometric processing such as image scaling, transformation, and rotation for frontal face images. This face recognition system identifies faces with 92% of accuracy for the 400 images of 40 different people.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.319-331
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• 2022

The latest global COVID-19 pandemic has made the use of facial masks an important aspect of our lives. People are advised to cover their faces in public spaces to discourage illness from spreading. Using these face masks posed a significant concern about the exactness of the face identification method used to search and unlock telephones at the school/office. Many companies have already built the requisite data in-house to incorporate such a scheme, using face recognition as an authentication. Unfortunately, veiled faces hinder the detection and acknowledgment of these facial identity schemes and seek to invalidate the internal data collection. Biometric systems that use the face as authentication cause problems with detection or recognition (face or persons). In this research, a novel model has been developed to detect and recognize faces and persons for authentication using scale invariant features (SIFT) for the whole segmented face with an efficient local binary texture features (DLBP) in region of eyes in the masked face. The Fuzzy C means is utilized to segment the image. These mixed features are trained significantly in a convolution neural network (CNN) model. The main advantage of this model is that can detect and recognizing faces by assigning weights to the selected features aimed to grant or provoke permissions with high accuracy.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1269-1278
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• 2002

The more high growth of knowledge, the more need personal identity technique. Fingerprint or iris of the eye identity techniques are already commercialized and used various field. Using human face recognition or authentication are not high performance yet. But application for an organism or face recognition are expected getting important. We propose a user recognition system by verifying similarity comparison of eye and lip component images which are splitted, calculated characteristic rate of each facial components and added weight to special formula. Through test proposed methods and analysis the result, we got a high recognition rate.

• Archives of design research
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• v.12 no.4
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• pp.129-137
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• 1999

We see that the Interactive Entertainment Industry on the internet has a great potential to grow in the 21st century. There will be many kinds of internet content. Internet contents can be classified with six categories such as identity, entertainment, learning, shopping, community. However, we see that shopping and community have a higher market share among the six. Recently, community has become more important in making an internet business sucessful, because it is valuable in creating virtual society in cyber space. A chatting program has been an effective means to form community. So we developed the animation graphic chatting program that functions to express an emotion effectively compared to the text chatting.

• Journal of the Korea Convergence Society
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• v.9 no.4
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• pp.47-55
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• 2018

In this paper, we propose a novel face recognition(FR) method that takes advantage of combining weighted deep local features extracted from multiple Deep Convolutional Neural Networks(DCNNs) learned with a set of facial local regions. In the proposed method, the so-called weighed deep local features are generated from multiple DCNNs each trained with a particular face local region and the corresponding weight represents the importance of local region in terms of improving FR performance. Our weighted deep local features are applied to Joint Bayesian metric learning in conjunction with Nearest Neighbor(NN) Classifier for the purpose of FR. Systematic and comparative experiments show that our proposed method is robust to variations in pose, illumination, and expression. Also, experimental results demonstrate that our method is feasible for improving face recognition performance.

• (The) Research of the performance art and culture
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• no.18
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• pp.223-255
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• 2009

This paper deals with the tradition and identity of physical expression(${\bar{a}}{\dot{n}}gika$ abhinaya) system in Indian traditional theatre and dance. The ${\bar{a}}{\dot{n}}gika$ abhinaya of Indian dance and theatre has been stylized through long terms and thereby defines their identity and peculiarity by its highly stylized expression techniques while following dramatic way($n{\bar{a}}tya$-dharmi). The ${\bar{a}}{\dot{n}}gika$ abhinaya is said to had been derived from the ritualistic practice of ancient Vedic period(B.C. 15th-B.C. 5th c.), which is most clearly exemplified in hand gesture(hasta mudra). In $N{\bar{a}}tya$ ${\acute{S}}astra$, ${\bar{a}}{\dot{n}}gika$ abhinaya is explained in detail. It is classified broadly into facial expression(mukhaja abhinaya), gesture expression(śārīra abhinaya), movement expression($cest{\bar{a}}krita$ abhinaya). Further, $N{\bar{a}}tya$ ${\acute{S}}astra$ divides their various usages by parts which include head, glance, eyes, nose, eyelid, cheek, lower lip, chin, mouth, hand, chest, waist, belly, hip. thigh, claf, foot. Besides, it explains diverse ways of foot movement($c{\bar{a}}ri$), standing poses(sthana), gait(gati) and their combined movements(mandala). Many forms of Indian traditional theatre and dance basically follows the rule of ${\bar{a}}{\dot{n}}gika$ abhinaya proposed in $N{\bar{a}}tya$ ${\acute{S}}astra$, which identifies their unique characteristics.