• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.332-336
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• 2010

There are so many successful applications to image processing systems in industries. In this study we propose a position detection system for used oil filter by using a line laser. We have been done on the development of line laser as interaction devices. A camera captures images of a display surface of a used oil filter and then a laser beam location is extracted from the captured image. This image is processed and used as a cursor position. We also discuss an algorithm that can distinguish the front part and rear part. In particular we present a robust and efficient linear detection algorithm that allows us to use our system under a variety lighting conditions, and allows us to reduce the amount of image parsing required to find a laser position by an order of magnitude.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.672-678
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• 2020

Ultra-high-speed images that accurately depict the minute movements of objects have become common as low-cost and high-performance cameras that can film at high speeds have emerged. In this paper, the proposed method removes unexpected noise contained in images after input at high speed, and then extracts an area of interest that can represent personal information, such as skin areas, from the image in which noise has been removed. In this paper, noise generated by abnormal electrical signals is removed by applying bilateral filters. A color model created through pre-learning is then used to extract the area of interest that represents the personal information contained within the image. Experimental results show that the introduced algorithms remove noise from high-speed images and then extract the area of interest robustly. The approach presented in this paper is expected to be useful in various applications related to computer vision, such as image preprocessing, noise elimination, tracking and monitoring of target areas, etc.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1361-1368
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• 2020

The system for counting the number of people has traditionally been implemented in various ways. Existing systems include infrared sensors, lasers, cameras, etc. In the case of such an existing system, there are restrictions on space such as ceilings and sides of walls. In this paper, we propose a method of detecting the footsteps of pedestrians using a piezoelectric mat containing a number of piezoelectric sensors and counting the number of pedestrians passing simultaneously by using the data collected from the piezoelectric mat. When pedestrians pass over piezoelectric mats, the collected sensor data was aggregated using SPI communication and transmitted to PC server using TCP/IP communication. Performance analysis shows that approximately 600 step data can be recognized with 99% accuracy. This is to overcome the shortcomings of other counting systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.83-95
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• 2022

This paper proposes a system that performs object detection and distance estimation for application to autonomous vehicles. Object detection is performed by a network that adjusts the split grid to the input image ratio using the characteristics of the recently actively used deep learning model YOLOv4, and is trained to a custom dataset. The distance to the detected object is estimated using a bounding box and homography. As a result of the experiment, the proposed method improved in overall detection performance and processing speed close to real-time. Compared to the existing YOLOv4, the total mAP of the proposed method increased by 4.03%. The accuracy of object recognition such as pedestrians, vehicles, construction sites, and PE drums, which frequently occur when driving to the city center, has been improved. The processing speed is approximately 55 FPS. The average of the distance estimation error was 5.25m in the X coordinate and 0.97m in the Y coordinate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.131-133
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• 2021

Recently, the average cost of education per child has increased compared to the annual birthrate, which has been decreasing, and the quality of education has also changed. In this paper, we aim to provide more efficient delivery for language learning using Unity's Buforia techniques. Using an application using a smartphone's camera based on Unity, it provides effective language development by inducing interest to learners through sound along with three-dimensional pictures. By providing such education, parents can gain satisfaction in providing high-quality education to their children. For children learning, smartphones have the effect of becoming educational elements, not just watching videos or playing games. Finally, by improving the quality of education, it gives satisfaction to parents and gives children who learn a language as well as the perception that smartphones serve as educational devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.35-40
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• 2021

People counting data is crucial for most business owners, since they can derive meaningful information about customers movement within their businesses. For example, owners of the supermarkets can increase or decrease the number of checkouts counters depending on number of occupants. Also, it has many applications in smart buildings, too. Where it can be used as a smart controller to control heating and cooling systems depending on a number of occupants in each room. There are advanced technologies like camera-based people counting system, which can give more accurate counting result. But they are expensive, hard to deploy and privacy invasive. In this paper, we propose a method and a hardware sensor for counting people passing through a passage or an entrance using IR Infrared sensors. Proposed sensor operates at low voltage, so low power consumption ensure long duration on batteries. Moreover, we propose a new method that distinguishes human body and other objects. Proposed method is inexpensive, easy to install and most importantly, it is real-time. The evaluation of our proposed method showed that when counting people passing one by one without overlapping, recall was 96% and when people carrying handbag like objects, the precision was 88%. Our proposed method outperforms IR Infrared based people counting systems in term of counting accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.469-472
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• 2022

With the recent development of intelligent transportation systems, various technologies applying deep learning technology are being used. To crackdown on illegal vehicles and criminal vehicles driving on the road, a vehicle type classification system capable of accurately determining the type of vehicle is required. This study proposes a vehicle type classification system optimized for mobile traffic control systems using YOLO(You Only Look Once). The system uses a one-stage object detection algorithm YOLOv5 to detect vehicles into six classes: passenger cars, subcompact, compact, and midsize vans, full-size vans, trucks, motorcycles, special vehicles, and construction machinery. About 5,000 pieces of domestic vehicle image data built by the Korea Institute of Science and Technology for the development of artificial intelligence technology were used as learning data. It proposes a lane designation control system that applies a vehicle type classification algorithm capable of recognizing both front and side angles with one camera.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.551-562
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• 2024

This study relates to a method and device for extracting and tracking moving objects. In particular, objects are extracted using different images between adjacent images, and the location information of the extracted object is continuously transmitted to provide accurate location information of at least one moving object. It relates to a method and device for extracting and tracking moving objects based on tracking moving objects. People tracking, which started as an expression of the interaction between people and computers, is used in many application fields such as robot learning, object counting, and surveillance systems. In particular, in the field of security systems, cameras are used to recognize and track people to automatically detect illegal activities. The importance of developing a surveillance system, that can detect, is increasing day by day.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.2
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• pp.18-25
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• 2008

The current display systems including TVs are going digital and large-sized, and high visual quality of those systems becomes a very important selling point in the current display system market. Thus, various researches have been carried out for enhancing the visual quality of digital display systems. One of the important digital image(or video) enhancement techniques is sharpness enhancement, and it is generally based on a transient improvement technique that reduces the edge transition time. However, this technique often generates overshoot and undershoot, which cause undesirable pixel-level changes around the transient improved edge. In this paper, we propose a new nonlinear filter-based adaptive shoot elimination method for effectively suppressing the overshoot and undershoot that occur in the transient improvement, so that we can obtain visually sharper and clearer digital images(or videos). The proposed method uses two orthogonal directional min/max nonlinear filters with an adaptive shoot elimination scheme in order to effectively suppress the visually sensitive overshoot and undershoot. Experimental results show that the proposed method suppresses the overshoot and undershoot almost perfectly while maintaining the effect of the transient improvement. The applications of the proposed method include digital TVs, digital monitors, digital cameras/camcoders, portable media players(PMP), etc.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.61-71
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• 2009

In this paper, we propose a low-cost and compact motion capture system which enables to play motion games in PS2(Play Station 2). Recently, motion capture systems which are being used as a part in film producing and making games are too expensive and enormous systems. Now days, motion games using common USB camera are slow and have two-dimension recognition. But PSD sensor has a few good points, such as fast and low-cost. In recently year, 3D motion capture systems using 2D PSD (Position Sensitive Detector) optic sensor for motion capturing have been developed. One is Multi-PSD motion capture system applying stereo vision and another is Single-PSD motion capture system applying optical theory ship. But there are some problems to apply them to motion games. The Multi-PSD is high-cost and complicated because of using two more PSD Camera. It is so difficult to make markers having omni-direction equal intensity in Single-PSD. In this research, we propose a new theory that solves aforementioned problems. It can measure 3D coordination if separated two marker's intensity is equal to. We made a system based on this theory and experimented for performance capability. As a result, we were able to develop a motion capture system which is a single, low-cost, fast, compact, wide-angle and an adaptable motion games. The developed system is expected to be useful in animation, movies and games.