• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.175-180
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• 2018

In this paper, a feature extraction and object recognition algorithm using only morphological operations is proposed. The morphological operations used in feature extraction are erosion and dilation, opening and closing combining erosion and dilation, and morphological edge and skeleton detection operation. In the process of recognizing an object based on features, a pooling operation is applied to reduce the dimension. Among various structuring elements, $3{\times}3$ rhombus, $3{\times}3$ square, and $5{\times}5$ circle are arbitrarily selected in morphological operation process. It has confirmed that the proposed algorithm can be applied in object recognition fields through experiments using Internet images.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.141-146
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• 2017

New infectious diseases such as MERS have been in need of many measures such as initial discovery, isolation, and crisis response. In addition, the culture of hospitals is changing, such as the general public 's visiting and Nursing Care Integration Services. However, as the qualifications and regulations of medical personnel in hospitals become rigid, overseas such as linens, wastes movements are replacing possible works with robots. we have developed a hospital logistics robot that can carry out various goods delivery within a hospital, and can move various kinds of objects safely to a desired location. In this thesis, we have studied a hospital logistics robot that can carry out various kinds of goods delivery within the hospital, and can move various kinds of objects such as waste, and linen safely to a desired location. The movement of a robot in a hospital may cause a collision between a person and an object, so that the collision must be prevented. In order to prevent collision, it is necessary to recognize whether or not an object exists in the movement path of the robot. And if there is an object, it should recognize whether it moves or not. In order to recognize human beings and objects, we recognize the person with face/body recognition technology and generate the context awareness of the object using 3D Vision image segmentation technology. We use the generated information to create a map that considers objects and person in the robot moving range. Thus, the robot can be operated safely and efficiently.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.256-259
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• 2016

The growth of mobile devices in Internet of Things (IoT) leads to a number of intelligent buildings related IoT applications. For instance, home automation controlling system uses client system such web apps on smartphone or web service to access the home server by sending control commands. The home server receives the command, then controls for instance the light system. The gateway based RESTful technology responsible for handling clients' requests attests an internet latency in case a large number of clients' requests submit toward the gateway increases. In this paper, we propose the design tasks of the IoT gateway for handling concurrency events. In the procedure of designing tasks, concurrency is best understood by employing multiple levels of abstraction. The way that is eminently to accomplish concurrency is to build an object-oriented environment with support for messages passing between concurrent objects. We also investigate the performance of event-driven architecture for building IoT gateway using node.js on one side and communication protocol based message-oriented middleware known as XMPP to handle communications of intelligent building control devices connected to the gateway through a centralized hub. The Node.JS is 40% faster than the traditional web server side features thread-based approach. The use of Node.js server-side handles a large number of clients' requests, then therefore, reduces delay in performing predefined actions automatically in intelligent building IoT environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.262-269
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• 2020

Recently, many attempts have been made to reduce the time required for payment in various shopping environments. In addition, for the Fourth Industrial Revolution era, artificial intelligence is advancing, and Internet of Things (IoT) devices are becoming more compact and cheaper. So, by integrating these two technologies, access to building an unmanned environment to save people time has become easier. In this paper, we propose a smart shopping cart system based on low-cost IoT equipment and deep-learning object-detection technology. The proposed smart cart system consists of a camera for real-time product detection, an ultrasonic sensor that acts as a trigger, a weight sensor to determine whether a product is put into or taken out of the shopping cart, an application for smartphones that provides a user interface for a virtual shopping cart, and a deep learning server where learned product data are stored. Communication between each module is through Transmission Control Protocol/Internet Protocol, a Hypertext Transmission Protocol network, a You Only Look Once darknet library, and an object detection system used by the server to recognize products. The user can check a list of items put into the smart cart via the smartphone app, and can automatically pay for them. The smart cart system proposed in this paper can be applied to unmanned stores with high cost-effectiveness.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.21-28
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• 2019

Internet of Things(IoT) is a technology or environment that collects data by attaching sensors to objects and transmits the collected information to each other through wired / wireless communication in real time. It is expected that when the Internet of objects is activated, many objects can identify and recognize each other by themselves and provide various services to facilitate our lives through mutual information exchange. In addition, the internet market for things is growing rapidly each year, and various IT technologies are expected to converge. In the Internet environment of objects, data exchange technology between object devices, that is, message protocol, is classified as one of important technologies. In this paper, we examine various lightweight message protocols suitable for the Internet environment of objects, and compare the reliability of the CoAP protocol structure with the MQTT protocol for a limited environment. Finally, we confirm the reliability of TCP / TLS and WebSockets-based CoAP transmission protocol of IETF's CoRE WG that can use various transport layers other than UDP in Internet environment including cloud infrastructure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1310-1316
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• 2021

Recently, with the development of artificial intelligence and IoT technology, the importance of video processing such as object tracking, medical imaging, and object recognition is increasing. In particular, the noise reduction technology used in the preprocessing process demands the ability to effectively remove noise and maintain detailed features as the importance of system images increases. In this paper, we provide a modified weight filter based on pixel matching in an AWGN environment. The proposed algorithm uses a pixel matching method to maintain high-frequency components in which the pixel value of the image changes significantly, detects areas with highly relevant patterns in the peripheral area, and matches pixels required for output calculation. Classify the values. The final output is obtained by calculating the weight according to the similarity and spatial distance between the matching pixels with the center pixel in order to consider the edge component in the filtering process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1159-1164
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• 2018

Recently, Internet use is increasing in various fields. Especially in the sudden disaster area, the role of Internet of things that can continuously monitor is getting bigger. In this study, the characteristics of the confined space and the environmental hazards are examined, and the Internet of the object which is being commercialized will be reviewed. Accidents in confined spaces are very high compared to other places, and it is very difficult to predict accidents. Recently, various attempts have been made to prevent accidents in confined spaces using the Internet of things. Especially, it detects the various gases that can occur in the closed space using sensors and sends them to the workers in real time, so that the risk can be detected in advance to minimize the risk. In this paper, we propose an effective disaster prevention plan using the Internet of things through the case study of the Internet for the prevention of accidents in a confined space.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.289-296
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• 2020

Software copyright are written in text form of documents and stored as files, so it is easy to expose on an illegal copyright. The IOT framework configuration and service environment are also evaluated in software structure and revealed to replication environments. Illegal copyright can be easily created by intelligently modifying the program code in the framework system. This paper deals with similarity comparison to determine the suspicion of illegal copying. In general, original source code should be provided for similarity comparison on both. However, recently, the suspected developer have refused to provide the source code, and comparative evaluation are performed only with executable code. This study dealt with how to analyze the similarity with the execution code and the circuit configuration and interface state of the system without the original source code. In this paper, we propose a method of analyzing the data of the object without source code and verifying the similarity comparison result through evaluation examples.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.675-681
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated in various fields, interest in video processing, which is the basis for automation such as object recognition and object classification, is increasing. Various studies have been conducted on noise removal in the video processing process, which has a significant impact on image quality and system accuracy and reliability, but there is a problem that it is difficult to restore images for areas with high impulse noise density. In this paper proposes a filter algorithm based on partial mask and Lagrange interpolation to restore the damaged area of impulse noise in the image. In the proposed algorithm, the filtering process was switched by comparing the filtering mask with the noise estimate and the purge weight was calculated based on the low frequency component and the high frequency component of the image to restore the image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.207-213
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• 2022

Recently, with the improvement of the performance of IoT technology and AI, automation and unmanned work are progressing in a wide range of fields, and interest in image processing, which is the basis of automation such as object recognition and object classification, is increasing. Image noise removal is an important process used as a preprocessing step in an image processing system, and various studies have been conducted. However, in most cases, it is difficult to preserve detailed information due to the smoothing effect in high-frequency components such as edges. In this paper, we propose an algorithm to restore damaged images in AWGN(additive white Gaussian noise) using fuzzy weights based on Gaussian distribution. The proposed algorithm switched the filtering process by comparing the filtering mask and the noise estimate with each other, and reconstructed the image by calculating the fuzzy weights according to the low-frequency and high-frequency components of the image.