• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.208-217
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• 2020

The classification of plant diseases by images captured by a camera sensor has been studied over past decades. A method that has gained much interest is to use image segmentation, from which statistical features are derived and analyzed by machine learning. Recently, deep learning has been adopted in this area. However, image segmentation is still a difficult task to achieve stable performance due to a variety of environmental variations. The end-to-end learning in neural network has a demerit that train images may be different from real images acquired in outdoor fields. To solve these problems, we propose superpixel-based disease classification method using end-to-end CNN (convolutional neural network) learning. Based on experiments performed on PlantVillage apple images, the classification accuracy is 98.29% and 92.43% for full-image and superpixel. As well, the multivariate F1-score is (0.98, 0.93). Therefore we validate that the method of using superpixel is comparable to that of full-image.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.724-733
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• 2017

Conventional methods of automatically recording Go game positions do not properly consider obstacles (hand or object) on a Go board during the Go game. If the Go board is blocked by obstacles, the position of a Go stone may not be correctly recognized, or the sequences of moves may be stored differently from the actual one. In the proposed algorithm, only the complete Go board image without obstacles is stored as a background image and the obstacle is recognized by comparing the background image with the current input image. To eliminate the phenomenon that the shadow is mistaken as obstacles, this paper proposes the new obstacle detection method based on the gradient image instead of the simple differential image. When there is no obstacle on the Go board, the background image is updated. Finally, the successive background images are compared to recognize the position and type of the Go stone. Experimental results show that the proposed algorithm has more than 95% recognition rate in general illumination environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.85-91
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• 2014

Nowadays, Dynamic lighting control and management skills are studied and used. If the system which is to manage multiple intelligent spot applied ubiquitous service technology is built with decision making and used in the complex intelligent space like a apartment then will improve energy efficiency and provide comfortability in optimal conditions. To solve this problem distributed autonomous control middleware and energy management system which process data gathering by zigbee mesh network and search proper services to save energy by the existing state of things is necessary. In paper we designed DDLEMS (Distributed Dynamic Lighting Energy Management System) that is to service duplex communication embedded by software based home server platform to provide mobile services in the smart place and support decision making about energy saving to the best use of wireless censor node and controled network, energy display devices.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.493-505
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• 2016

Among modern computer vision and video surveillance systems, the pedestrian counting system is a one of important systems in terms of security, scheduling and advertising. In the field of, pedestrian counting remains a variety of challenges such as changes in illumination, partial occlusion, overlap and people detection. During pedestrian counting process, the biggest problem is occlusion effect in crowded environment. Occlusion and overlap must be resolved for accurate people counting. In this paper, we propose a novel pedestrian counting system which improves existing pedestrian tracking method. Unlike existing pedestrian tracking method, proposed method shows that average filter tracking method can improve tracking performance. Also proposed method improves tracking performance through frame compensation and outlier removal. At the same time, we keep various information of tracking objects. The proposed method improves counting accuracy and reduces error rate about S6 dataset and S7 dataset. Also our system provides real time detection at the rate of 80 fps.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.37-42
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• 2012

LED is just a semiconductor which can produce light. Currently, there are active research works on LED lighting technologies according to the growth of energy-saving environmental industry. Especially, LED communication is one of the active research works in these fields. In this paper, we design a LED communication-based multi-hop transmission wireless network system. The designed system consists of a transmission circuit system(transmitter) using LED and a receiving circuit system(receiver) using PD(photo detector) and OP-Amp, and relay system which can support multi-hop wireless network service with PD, OP-Amp, and LED, respectively. The experiments for the designed system are performed as follows. One computer is connected at the end of transmitter and receiver, respectively. There are two relays between transmitter and receiver, and text files are transmitted continuously by using text transmission programming. In this experiment, we test the performance with various baud rates, transmission ranges.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.119-124
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• 2014

In this paper, we propose the active rule system applying with emotional margin for power saving control. The proposed system in this paper is a part of the system which derives smart power saving by adjusting the illuminance using active rules within compromising the user's emotion. For this, we set the specific range of standard illuminance and the lower bound of user's emotional margin of illuminance based on measurements and analysis, and use these data in design of active rules. And then, we design and implement the active rule system using mobile agent. The mobile agent in the proposed system migrates to the destination sensor nodes, acquires and transmits sensor data according to the purpose and needs through the active rules, and directly executes the actions corresponding to the optional events(changed sensor data and/or time etc.). And then, we show the potential applicability of the proposed active rule system in various active sensor network applications through the interaction with the rule base and mobile sensor network middleware system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.157-163
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• 2013

In this paper, we propose a human detection technique using thermal imaging camera. The proposed method is useful at night or rainy weather where a visible light imaging cameras is not able to detect human activities. Under the observation that a human is usually brighter than the background in the thermal images, we estimate the preliminary human regions using the statistical confidence measures in the gray-level, brightness histogram. Afterwards, we applied Gaussian filtering and blob labeling techniques to remove the unwanted noise, and gather the scattered of the pixel distributions and the center of gravities of the blobs. In the final step, we exploit the aspect ratio and the area on the unified object region as well as a number of the principal components extracted from the object region images to determine if the detected object is a human. The experimental results show that the proposed method is effective in environments where visible light cameras are not applicable.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.153-159
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• 2014

In this paper, we propose the Distributed Power Saving Control System that enables the active and intelligent control(on/off and/or dimming control) of the lightning device using sensors and mobile agents. The proposed system is effective for energy saving and induces cost reductions in design and development of power saving control system as adding remote-monitoring or controlling functions is easier with the application of a variety of active rules. Moreover, the system improves the effectiveness of the acquired sensing data by real-time event handling and device controlling using a mobile agent based sensor network middleware that regularize the contextual information or a user's emotion. The results of this paper present the potential applicability of the proposed distributed control system using mobile agent in various active sensor network applications.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.67-82
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• 2020

This study is based on the screen composition(shot size, split screen, candidate placement, lighting, stage) that fits the discussion process (round table, sitting, standing method) adopted from the 19th presidential candidates' TV joint discussion to analyze the adequacy and limitations of the methodology(design, candidate background, etc.). In addition, the progress and screen composition of the 45th US Presidential Candidates Debate in 2016 and the 25th Presidential Candidates of France TV Joint Debate in 2017 have been analyzed to compare and contrast the methods used in Korea. Through this, we apply the screening method to the 20th Presidential Candidate TV Joint Debate, which will be held in 2022, to fit the fixed discussion process that can fully identify candidates' qualities, policies, and vision.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.62-69
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• 2017

Accurate detection of traffic lights is very important for the advanced driver assistance system (ADAS). There have been many research developments in this area. However, conventional of image processing methods are usually sensitive to varying illumination conditions. This paper proposes a traffic light detection algorithm to overcome this situation. The proposed algorithm first detects the candidates of traffic light using the proposed color map and hue-saturation-value (HSV) Traffic lights are then detected using the conventional histogram of oriented gradients (HOG) descriptor and support vector machine (SVM). Finally, the proposed Multilayer HOG descriptor is used to determine the direction information indicated by traffic lights. The proposed algorithm shows a high detection rate in real-time.