• Journal of the Optical Society of Korea
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• v.14 no.4
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• pp.388-394
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• 2010

In this paper the object recognition performance of a photon counting integral imaging system is quantitatively compared with that of a conventional gray scale imaging system. For 3D imaging of objects with a small number of photons, the elemental image set of a 3D scene is obtained using the integral imaging set up. We assume that the elemental image detection follows a Poisson distribution. Computational geometrical ray back propagation algorithm and parametric maximum likelihood estimator are applied to the photon counting elemental image set in order to reconstruct the original 3D scene. To evaluate the photon counting object recognition performance, the normalized correlation peaks between the reconstructed 3D scenes are calculated for the varied and fixed total number of photons in the reconstructed sectional image changing the total number of image channels in the integral imaging system. It is quantitatively illustrated that the recognition performance of the photon counting integral imaging system can be similar to that of a conventional gray scale imaging system as the number of image viewing channels in the photon counting integral imaging (PCII) system is increased up to the threshold point. Also, we present experiments to find the threshold point on the total number of image channels in the PCII system which can guarantee a comparable recognition performance with a gray scale imaging system. To the best of our knowledge, this is the first report on comparisons of object recognition performance with 3D photon counting & gray scale images.

• Journal of Environmental Science International
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• v.17 no.1
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• pp.77-83
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• 2008

The purpose of this study was to develop the national park visitor counting system using the ubiquitous sensor network. This system is composed of a sensor node, sink node, gateways, CDMA module, server, and clients. The results of the study were: 1) stable data transmission distance was possible within 100 meters between sensor nodes, 2) the developed counting sensor system showed a network communication stability level of 88.3 percent in 1.2m wide trails. When installed in concentrate use areas or forks of national parks, the visitor counting system will not only contribute to provide reliable visitor counting, but also to improve the quality of national park visitor service, to manage park facilities and natural resources more efficiently, to achieve an information oriented national park system.

• Journal of Environmental Health Sciences
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• v.41 no.5
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• pp.299-304
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• 2015

Objectives: A people-counting system measures real-time occupancy through motion detection. Accurate people-counting can be used to calculate suitable ventilation demands. This study determined the optimum motion threshold for a people-counting system. Methods: In a closed room with two occupants moving constantly, different thresholds were tested for the accuracy of a people-counting system. The experiments were conducted at 150, 300, 450 and 600 lux. These levels of brightness included the illumination levels of most public indoor areas. The experiments were repeated with three types of clothing coloration. Results: Overall, a threshold of 16 provided the lowest mean error percentage for the people-counting system. Brightness and clothing color did not have a significant impact on the results. Conclusion: A people-counting system could be used with threshold of 16 for most indoor environments.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.69-75
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• 2014

Existing People Counting System using a single overhead mounted camera has limitation in object recognition and counting in various environments. Those limitations are attributable to overlapping, occlusion and external factors, such as over-sized belongings and dramatic light change. Thus, this paper proposes the new concept of People Counting System by Facial Age Group using two depth cameras, at overhead and frontal viewpoints, in order to improve object recognition accuracy and robust people counting to external factors. The proposed system is counting the pedestrians by five process such as overhead image processing, frontal image processing, identical object recognition, facial age group classification and in-coming/out-going counting. The proposed system developed by C++, OpenCV and Kinect SDK, and it target group of 40 people(10 people by each age group) was setup for People Counting and Facial Age Group classification performance evaluation. The experimental results indicated approximately 98% accuracy in People Counting and 74.23% accuracy in the Facial Age Group classification.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.103-109
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• 2018

Purpose: This study has been conducted to develop a potato yield monitoring system, consisting of a segmentation algorithm to detect potatoes scattered on a soil surface and a counting system to count the number of potatoes and convert the data from two-dimensional images to masses. Methods: First, a segmentation algorithm was developed using top-hat filtering and processing a series of images, and its performance was evaluated in a stationary condition. Second, a counting system was developed to count the number of potatoes in a moving condition and calculate the mass of each using a mass estimation equation, where the volume of a potato was obtained from its two-dimensional image, and the potato density and a correction factor were obtained experimentally. Experiments were conducted to segment potatoes on a soil surface for different potato sizes. The counting system was tested 10 times for 20 randomly selected potatoes in a simulated field condition. Furthermore, the estimated total mass of the potatoes was compared with their actual mass. Results: For a $640{\times}480$ image size, it took 0.04 s for the segmentation algorithm to process one frame. The root mean squared deviation (RMSD) and average percentage error for the measured mass of potatoes using this counting system were 12.65 g and 7.13%, respectively, when the camera was stationary. The system performance while moving was the best in L1 (0.313 m/s), where the RMSD and percentage error were 6.92 g and 7.79%, respectively. For 20 newly prepared potatoes and 10 replication measurements, the counting system exhibited a percentage error in the mass estimation ranging from 10.17-13.24%. Conclusions: At a travel speed of 0.313 m/s, the average percentage error and standard deviation of the mass measurement using the counting system were 12.03% and 1.04%, respectively.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.419-424
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• 2004

Various radiation counters have been using to determine radioactivity of radwastes for disposal. A radiation counting system was set up using a radiation detector chosen in this study and its stability was investigated through the periodic determination of background and counting efficiencies in accordance with a quality control program to increase the confidence level. The average background level for the $\gamma$-spectrometer was 1.59 cps and the average counting level for the standard sample was 45248 Ops within $2{\sigma}$ confidence levels. The average alpha background level for the low background ${\alpha}{\beta}$ counting system was 0.31 cpm and the efficiency for alpha counting was 34.38%. The average beta background level for the ${\alpha}{\beta}$ counting system was 1,30 cpm and the efficiency for beta counting was 46.5%, The background level in the region of 3H and 14C for the liquid scintillation counting system was 2.52 and 3.31 cpm and the efficiency for alpha counting was 58.5 and 95.6%, respectively. The minimum detectable activity for the$\gamma$-spectrometer was found to be 3.2 Bq/$m\ell$ and 3.8 Bq/$m\ell$ for the liquid scintillation counter, and 20.5 and 23.0 Bq/$m\ell$, respectively for the $\alpha$ and $\beta$ counting system.

• Journal of the Korean Dietetic Association
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• v.5 no.1
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• pp.64-73
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• 1999

Carbohydrate(CHO) counting is a meal planning approach used with diabetic patients that focuses on carbohydrate as the primary nutrient affecting post-prandial glycemic response. However, it has not been used in meal management of diabetic patients in Korea. CHO counting can be used by clients with type 1 and 2 diabetes. The purpose of the study was to determine the barriers to utilize the CHO counting when three levels of CHO counting were educated to type 2 diabetic patients who started continuous subcutaneous insulin infusion (CSⅡ) therapy by nutrition lectures and counseling. And the CHO-to-insulin ratios were determined for the individual patients who followed the carbohydrate counting as a meal management, and the factors to influence the CHO-to-insulin ratios were selected through the stepwise regression analysis. Twenty- four subjects were received three lectures, and one or two nutritional counseling for a month. The average age of the subjects was 50.7 years, and the duration of diabetes was 9.4 years. Their body mass index (BMI) was 21.5 kg/$m^2$. The difficulties of using CHO counting were 1) confusing the CHO exchange system to diabetic food exchange system, 2) lack of basic nutrition and not distinguishing nutrients such as CHO, fat and calorie, and 3) lack of motivation to make effort to count and record the amount of carbohydrates eaten. Nutritional counseling replenished the nutrition education and made patients practice CHO counting. Average CHO-to-insulin ratios at breakfast, lunch and dinner were 4.1$\pm$3.3, 2.9$\pm$2.6 and 2.9$\pm$3.0units/23g of CHO, respectively. CHO-to-insulin ratios were influenced by gender, age, BMI, post-prandial blood glucose levels and post-prandial c-peptide levels. The effective education and nutritional counseling of CHO counting can make CHO counting applicable to type 2 diabetic patients as meal management for improving glycemic control with less hypoglycemic episode.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.4
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• pp.652-657
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• 2013

In this study, we developed a counting method for non-contact ID cards using an optical fiber displacement sensor instead of the traditionally used friction counting method. The proposed method has the advantage of high speed and automated measurement. For counting non-contact ID cards, an H-type optical fiber sensor, jig part, and counting program are developed separately to build the system and adjust it. Through the experimental test results, it was confirmed that counting is possible with one type of international ID card and one type of financial security card based on ISO7810. Furthermore, by applying the proposed method to 100 ID cards 100 times repeatedly, it was confirmed that it has high accuracy and an error ratio of 0%. We experimentally demonstrated that the proposed counting method for non-contact ID cards using an optical fiber displacement sensor can perform measurements with high accuracy and high speed.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1890-1897
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• 2021

People counting is an important technology to provide application services such as smart home, smart building, smart car, etc. Due to the social distancing of COVID-19, the people counting technology attracted public attention. People counting system can be implemented in various ways such as camera, sensor, wireless, etc. according to service requirements. People counting system using WiFi AP uses WiFi CSI data that reflects multipath information. This technology is an effective solution implementing indoor with low cost. The conventional WiFi CSI-based people counting technologies have low accuracy that obstructs the high quality service. This paper proposes a deep learning people counting system based on WiFi CSI data. Data preprocessing using auto-encoder, data augmentation that transform WiFi CSI data, and a proposed deep learning model improve the accuracy of people counting. In the experimental result, the proposed approach shows 89.29% accuracy in 6 subjects.