• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.441-447
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• 2023

Intravenous infusion therapy is a standard nursing procedure in medical institutions that provides patients with drugs, fluids, blood, and nutrients into the patient's mucus. It is mainly performed and managed by nurses. Additionally, it is an injection method that injects drugs directly into the blood vessels, and is used to achieve rapid results in emergency situations, and quick and accurate effects can be expected. Even experienced nurses through education and training often make mistakes, which can not only cause discomfort to patients but also cause various problems that threaten patient safety. Various studies are being conducted to reduce the pain caused by these mistakes. This paper acquired images of veins on the back of the hands of three subjects through an image detection device and conducted a study to derive an algorithm to provide clear vein images through image processing of the collected images. To sharpen the acquired vein images, existing algorithms Histogram Equalization, CLAHE, and Unsharp Masking were selected and combined. A histogram graph was used to compare images derived by applying individual algorithms and algorithm combinations to images. The histogram graph was checked by calculating the difference between the minimum and maximum values of distributed pixels and averaging them. The algorithm combination presented in this paper was 209.1, which was higher than the average values of individual algorithms of 138.7, 132.3, and 126.2, and it was confirmed that visibility was good even in actual images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.3
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• pp.417-429
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• 1998

The advance of the MPEG (Moving Picture Expert Group) and the DSP (Digital Signal Processing) technologies lead the emergence of the information appliances, which are gradually digitalized and embedded the high-speed networking function. However, there are some difficulties in establishing any one specific model, since standardization of the scale and function of home ATM network is being progressed by standardization organizations and no absolute model has been defined. This paper consider topologies for a home ATM network, such a star-type, tree-type, and mesh-type topology, by comparing the structure, functional characteristics and performance. From this analysis we suggest the design method of the home ATM network.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.113-114
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• 2023

가정용 생활 쓰레기 수거 작업은 야간이나 이른 새벽에 이루어지고 있어 환경미화원의 안전사고와 수거 차량으로 인한 소음 문제가 빈번하게 발생한다. 본 논문에서는 딥러닝 기반의 영상 인식을 활용하여 종량제 봉투를 인식하고 수거가 가능한 생활 쓰레기 수거 로봇의 설계를 제시한다. 제시하는 생활 쓰레기 수거 로봇은 지정 구역을 자율주행하며 로봇에 장착된 카메라를 이용해 학습된 모델을 기반으로 가정용 쓰레기 종량제 봉투를 검출한다. 이를 통해 처리 대상으로 지정된 종량제 봉투와 로봇 팔 사이의 거리를 카메라를 활용하여 얻은 깊이 정보와 2차원 좌표를 토대로 목표 위치를 예측해 로봇 팔의 관절을 제어하여 봉투를 수거한다. 해당 로봇은 생활 쓰레기 수거 작업 과정에서 환경미화원을 보조하여 미화원의 안전 확보와 소음 저감을 위한 기기로 활용될 수 있다.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.9
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• pp.381-392
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• 2013

During the last decade, the multitude of advances attained in terminal computers, along with the introduction of mobile hand-held devices, and the deployment of high speed networks have led to a recent surge of interest in Quality of Service (QoS) for video applications. The main difficulty is that mobile devices experience disparate channel conditions, which results in different rates and patterns of packet loss. One way of making more efficient use of network resources in video services over wireless channels with heterogeneous characteristics to heterogeneous types of mobile device is to use a scalable video coding (SVC). An SVC divides a video stream into a base layer and a single or multiple enhancement layers. We have to ensure that the base layer of the video stream is successfully received and decoded by the subscribers, because it provides the basis for the subsequent decoding of the enhancement layer(s). At the same time, a system should be designed so that the enhancement layer(s) can be successfully decoded by as many users as possible, so that the average QoS is as high as possible. To accommodate these characteristics, we propose an efficient transmission scheme which incorporates SVC-aware dual-channel repetition to improve the perceived quality of services. We repeat the base-layer data over two channels, with different characteristics, to exploit transmission diversity. On the other hand, those channels are utilized to increase the data rate of enhancement layer data. This arrangement reduces service disruption under poor channel conditions by protecting the data that is more important to video decoding. Simulations show that our scheme safeguards the important packets and improves perceived video quality at a mobile device.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.889-898
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• 2013

Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.449-456
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• 2019

This paper is a study on the construction of a wall-climbing mobile robot using vacuum suction and wheel-type movement, and a comparison of the performance of an automatic wall crack detection algorithm based on machine learning that is suitable for such an embedded environment. In the embedded system environment, we compared performance by applying recently developed learning methods such as YOLO for object learning, and compared performance with existing edge detection algorithms. Finally, in this study, we selected the optimal machine learning method suitable for the embedded environment and good for extracting the crack features, and compared performance with the existing methods and presented its superiority. In addition, intelligent problem - solving function that transmits the image and location information of the detected crack to the manager device is constructed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.586-589
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• 2015

A computer presentation system by using hand-motion identification rules is proposed. To identify hand motions of a presenter, a face region is extracted first using haar classifier. A motion status(patterns) and position of hands is discriminated using the center of gravities of user's face and hand after segmenting the hand area on the YCbCr color model. User's hand is applied to the motion detection rules and then presentation control command is then executed. The proposed system utilizes the motion identification rules without the use of additional equipment and it is then capable of controlling the presentation and does not depend on the complexity of the background. The proposed algorithm confirmed the stable control operation via the presentation of the experiment in the dark illumination range of indoor atmosphere (lx) 15-20-30.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.900-902
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• 2015

In the modern society, according to the advancement in digital image processing technology, edge detection is being utilized in various application sectors such as smart device and medical, etc. In existing edge detection methods, there are Sobel, Prewitt, Roberts and Laplacian, etc, which uses the mask. These previous methods are easy to implement but shows somewhat insufficient results. Therefore, in order to compensate the problems of existing methods, in this paper, an algorithm that detects the edge using the local mask and morphological operation was proposed and the detection performance was compared against the previous methods.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.117-124
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• 2014

Cluttered background is a major obstacle in developing salient object detection and tracking system for mobile device captured natural scene video frames. In this paper we propose a context aware feature vector selection model to provide an efficient noise filtering by machine learning based classifiers. Since the context awareness for feature selection is achieved by searching nearest neighborhoods, known as NP hard problem, we apply a fast approximation method with complexity analysis in details. Separability enhancement in feature vector space by adding the context aware feature subsets is studied rigorously using principal component analysis (PCA). Overall performance enhancement is quantified by the statistical measures in terms of the various machine learning models including MLP, SVM, Naïve Bayesian, CART. Summary of computational costs and performance enhancement is also presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.889-890
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• 2016

Existing machine-to-machine collaboration system is a centralized structure system fo built OpenWrt and a Web server on the router. But scarce resources of the router are getting more requests from the collaboration client when a problem has occurred with increasing probability of a client object, the higher the traffic. In this paper, in order to solve the problem, we propose a distributed system utilizing Machine Socialization cooperation algorithm. The MCU attached to the machine to minimize the traffic occurrence probability and loss of the data by processing to distribute the data between the server and the client. Also improve the response speed between the server and the client and the operation stop caused by the loss of data. The proposed system will be utilized if the IoT field will be high efficiency compared to existing systems.