• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1996.06c
• /
• pp.773-779
• /
• 1996

Dried oak mushroom have complex and various visual features. Grading and sorting of dried oak mushrooms has been done by the human expert. Though actions involved in human grading looked simple, a decision making underneath the simple action comes from the result of the complex neural processing of the visual image. Through processing details involved in human visual recognition has not been fully investigated yet, it might say human can recognize objects via one of three ways such as extracting specific features or just image itself without extracting those features or in a combined manner. In most cases, extracting some special quantitative features from the camera image requires complex algorithms and processing of the gray level image requires the heavy computing load. This fact can be worse especially in dealing with nonuniform, irregular and fuzzy shaped agricultural products, resulting in poor performance because of the sensitiveness to the crisp criteria or specific ules set up by algorithms. Also restriction of the real time processing often forces to use binary segmentation but in that case some important information of the object can be lost. In this paper, the neuro net based real time recognition algorithm was proposed without extracting any visual feature but using only the directly captured raw gray images. Specially formated adaptable size of grids was proposed for the network input. The compensation of illumination was also done to accomodate the variable lighting environment. The proposed grading scheme showed very successful results.

• Advances in environmental research
• /
• v.12 no.2
• /
• pp.113-122
• /
• 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 Contents Association
• /
• v.10 no.9
• /
• pp.1-8
• /
• 2010

In this paper, we propose a large scale entertainment system based on gesture recognition for learning Chinese character contents. The system is consisted of parts that forecast user's posture in two infrared images and part that recognize gestures from continuous poses. And we can divide and acquire in front side pose and side pose about one pose in each IR camera. This entertainment system is immersive in nature and convenient for its gestures based controlling system. Also, it can maximize information transmission because induce immersion and interest using two large size displays and various multimedia elements. The learning Chinese character contents can master Chinese character naturally because give interest to user and supply game and education at the same time. Therefore, it can expect synergy effect that can learn playing to user combining with large entertainment system based on gesture recognition.

• Convergence Security Journal
• /
• v.12 no.6
• /
• pp.31-37
• /
• 2012

Today, the core technology of an automobile is becoming to IT-based convergence system technology. To cope with many kinds of situations and provide the convenience for drivers, various IT technologies are being integrated into automobile system. In this paper, we propose an convergence system, which is called Augmented Driving System (ADS), to provide high safety and convenience of drivers based on image information processing. From imaging sensor, the image data is acquisited and processed to give distance from the front car, lane, and traffic sign panel by the proposed methods. Also, a converged interface technology with camera for gesture recognition and microphone for speech recognition is provided. Based on this kind of system technology, car accident will be decreased although drivers could not recognize the dangerous situations, since the system can recognize situation or user context to give attention to the front view. Through the experiments, the proposed methods achieved over 90% of recognition in terms of traffic sign detection, lane detection, and distance measure from the front car.

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.2
• /
• pp.91-96
• /
• 2022

At the current camera-based technology level, sensor-based basic life pattern recognition technology has to suffer inconvenience to obtain accurate data, and commercial band products are difficult to collect accurate data, and cannot take into account the motive, cause, and psychological effect of behavior. the current situation. In this paper, radar technology for life pattern recognition is a technology that measures the distance, speed, and angle with an object by transmitting a waveform designed to detect nearby people or objects in daily life and processing the reflected received signal. It was designed to supplement issues such as privacy protection in the existing image-based service by applying it. For the implementation of the proposed system, based on TI IWR1642 chip, RF chipset control for 60GHz band millimeter wave FMCW transmission/reception, module development for distance/speed/angle detection, and technology including signal processing software were implemented. It is expected that analysis of individual life patterns will be possible by calculating self-management and behavior sequences by extracting personalized life patterns through quantitative analysis of life patterns as meta-analysis of living information in security and safe guards application.

• The Journal of Society for e-Business Studies
• /
• v.17 no.3
• /
• pp.1-14
• /
• 2012

As the techniques of electronic and information are advancing, the computing power of a smart phone is becoming more powerful and the storage capacity of a smart phone is becoming larger. As the result, various new useful services are becoming available on smart phones. The context-aware service and mobile augmented reality have recently been the most popular research topics. For those newly developed services, identifying the object in the picture taken by the camera on the phone performs an extremely important role. So, many researches of identifying pictures have been published and most of them are based on the time consuming image recognition techniques. On the contrary, this paper introduces a very fast and effective method of identifying the objects on the photo making use of the sensor data obtained from the smart phone and electronic maps. Our method estimates the line of sight of the camera with the location and orientation information provided by the smart phone. Then it finds any element of the map which intersects the line of sight. By investigating those intersecting elements, our method identifies the objects on the photo.

• Journal of Service Research and Studies
• /
• v.5 no.2
• /
• pp.93-101
• /
• 2015

Today, various access security technology appeared in this society as a result of the informatization and automation. Most building, floor, or door security certification system for the office units are installed, but there are many inconvenient matters. In order to minimises this, we used the face recognition function via the camera, and various sensors. In this paper, I designed the access security system through physical computing which Arduino offered, facial recognition program, and Twitter. Check that the personal information stored in the individual RFID tag is matched to the personal information stored on the existing server. Face recognition program input the face using a camera, and allow to confirm the identity. The system's abnormal or when the unauthenticated person is to penetrate, the system transmits the Twitter status message to the manager. It was designed continuously to monitor the status in real time in this way.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.10
• /
• pp.505-512
• /
• 2024

As the need for hygiene management increases due to COVID-19, the importance of non-contact services is gaining attention. Hands, a tool for expressing intentions and conveying information, are emerging as an alternative to computer input devices such as the keyboard and mouse. In this study, we propose a method to address public health problems that arise when using unmanned ordering machines by controlling a computer using hand gestures detected through a camera. The focus is on identifying frequently used hand gestures, especially the bending of the index finger. To this end, we develop a non-contact input device using the MediaPipe framework and the long short-term memory (LSTM) model. This approach can identify hand gestures in three-dimensional space and provides scenarios that can be applied to the fields of virtual reality (VR) and augmented reality (AR). It offers improved public health and user experience by presenting methods that can be applied to various situations such as navigation systems and unmanned ordering machines.

• Journal of the Korea Convergence Society
• /
• v.11 no.7
• /
• pp.19-24
• /
• 2020

WHO declared a global pandemic on March 11th for Corona 19. However, there is a situation where you have to go to building for face-to-face education or seminars for economic and social activities. The first check method of COVID-19 infection is to measure body temperature, so the primary entrance and exit is blocked for near-field body temperature measurement. However, since it is troublesome to check directly, thermal camera is installed at the entrance of the building, and body temperature is measured indirectly using the infrared camera to control access. In case of middle and high schools, universities, and lifelong education center, we need a system that is possible to interoperate with attendance checks and automatically recognizes whether to wear masks and can authenticate students. We proposed the system that is to confirm whether to wear a mask with a camera that is embedded in a smart mirror, and that authenticates the user through voice recognition of the user who wants to enter the building by using voice recognition technology and determines whether to enter them or not. The proposed system can check attendance if it is linked with near-field temperature measurement and attendance check APP of student's smart phone.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.2
• /
• pp.8-14
• /
• 2020

Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.