• Communications for Statistical Applications and Methods
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• v.18 no.3
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• pp.301-317
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• 2011

Statistical and probabilistic behaviors of fibers forming fiber webs of all kinds are of great significance in the determination of the uniformity and physical properties of the webs commonly found in many industrial products such as filters, membranes and non-woven fabrics. However, in studying the spatial geometry of the webs the observations must be theoretically as well as experimentally confined within a specified unit area. This paper provides a general theory and framework for computer simulation for quantifying the fiber segments bounded by the unit area in consideration of the "edge effects" resulting from the truncated length segments within the boundary. The probability density function and the first and second moments of the length segments found within the counting region were derived by properly defining the seeding region and counting region.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1892-1897
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• 2017

This paper proposes a finger counting algorithm for a hand with stuck fingers. The proposed algorithm is based on the fact that straight line type shadows are inevitably generated between fingers. It divides the hand region into the thumb region and the four fingers region for effective shadow detection, and generates an edge image in each region. Projection curves are generated by appling a line detection and a projection technique to each edge image, and the peaks of the curves are detected as candidates for finger shadows. And then peaks due to finger shadows are extracted from them and counted. In the finger counting experiment on hand images expressing various shapes with stuck fingers, the counting success rate is from 83.3% to 100% according to the number of fingers, and 93.1% on the whole. It also shows that if hand images are generated under controlled conditions, the failure cases can be sufficiently improved.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.4
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• pp.415-420
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• 2017

In this paper, an algorithm for object counting via a conveyor system using machine vision is suggested. Object counting systems using image processing have been applied in a variety of industries for such purposes as measuring floating populations and traffic volume, etc. The methods of object counting mainly used involve template matching and machine learning for detecting and tracking. However, operational time for these methods should be short for detecting objects on quickly moving conveyor belts. To provide this characteristic, this algorithm for image processing is a region-based method. In this experiment, we counted young abalone shells that are similar in shape, size and color. We applied a characteristic conveyor system that operated in one direction. It obtained information on objects in the region of interest by comparing a second frame that continuously changed according to the information obtained with reference to objects in the first region. Objects were counted if the information between the first and second images matched. This count was exact when young shells were evenly spaced without overlap and missed objects were calculated using size information when objects moved without extra space. The proposed algorithm can be applied for various object counting controls on conveyor systems.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1161-1166
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• 2011

A camera is mounted vertically downwards viewing the people heads from the top. This configuration is successful in people counting technique especially when only a few isolated people pass through a counting region in a non-crowded situation. Thus, this paper describes object counting which detects and count moving people using mixture of gaussian and motion vector. This method is intended to estimates the number of people in outdoor environment. This method use single gaussian background modeling which is more robust an noise and has adaptiveness. The experimental results that is based on mixture of gaussian and motion vector is also helpful to design intelligent surveillance.

• Journal of Broadcast Engineering
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• v.22 no.4
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• pp.448-461
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• 2017

This paper proposes a vehicle counting and speed estimation method for traffic situation analysis in road CCTV videos. The proposed method removes a distortion in the images using Inverse perspective Mapping, and obtains specific region for vehicle counting and speed estimation using lane detection algorithm. Then, we can obtain vehicle counting and speed estimation results from using optical flow at specific region. The proposed method achieves stable accuracy of 88.94% from several CCTV images by regional groups and it totally applied at 106,993 frames, about 3 hours video.

• 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 Broadcast Engineering
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• v.22 no.1
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• pp.70-77
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• 2017

Among available people counting methods, map-based approaches based on moving interest points have shown good performance. However, the stationary people counting is challenging in such methods since all static points of interest are considered as background. To include stationary people in counting, it is needed to discriminate between the static points of stationary people and the background region. In this paper, we propose a people counting method based on using both moving and static points. The proposed method separates the moving and static points by motion information. Then, the static points of the stationary people are classified using foreground mask processing and point pattern analysis. The experimental results reveal that the proposed method provides more accurate count estimation by including stationary people. Also, the background updating is enabled to solve the static point misclassification problem due to background changes.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.247-257
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• 2023

Precise counting of cell number stands in important position within clinical and research laboratories. Conventional methods such as hemocytometer, migration/invasion assay, or automated cell counters have limited in analytical time, cost, and accuracy., which needs an alternative way with time-efficient in-situ approach to broaden the application avenue. Here, we present simple coding-based cell counting method using image analysis tool, freely available image software (ImageJ). Firstly, we encapsulated RFP-expressing bacteria in a droplet using microfluidic device and automatically performed fluorescence image-based analysis for the quantification of cell numbers. Also, time-lapse images were captured for tracking the change of cell numbers in a droplet containing different concentrations of antibiotics. This study confirms that our approach is approximately 15 times faster and provides more accurate number of cells in a droplet than the external analysis program method. We envision that it can be used to the development of high-throughput image-based cell counting analysis.

• Journal of radiological science and technology
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• v.46 no.5
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• pp.401-408
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• 2023

Thyroid uptake measurements can be subject to measurement errors due to the scoping and positioning of the thyroid gland. To compensate for these limitations, the clinical utility of the thyroid simultaneous counting method as an alternative to thyroid uptake measurement was analyzed and evaluated experimentally through quantitative analysis of images acquired after thyroid scanning. Experimental data were obtained using a Gamma camera (GE infinia), a thyroid uptake system (KOROID 1), and a thyroid neck phantom. Based on the thyroid uptake rate of 1-5% according to the protocol of thyroid scan test (^99mTcO₄ - , 370 MBq) in normal results, ^99mTcO₄ - was set in the range of 3.7-18.5 MBq (Matrix: 256×256, Scan time: 1 min, collimator: pin hole, phantom-collimator distances: 7 cm). The acquired images were corrected for the attenuation of isotopes due to the set-up time and half-life by applying the Auto Region of interest (ROI) drawing system, and the significance of the experimental results was evaluated by Multiple linear regression analysis (SPSS, ver. 22, IBM). The thyroid uptake rate showed a significant correlation between the dose and the measured counts when using the thyroid uptake system equipment. Meanwhile, the quantitative analysis counts of phantom images using Gamma camera also showed a significant correlation. Thus confirmed that the correlation between these two experiments was statistically significant (P<0.05). The simultaneous counting protocol, which indirectly measures thyroid uptake from thyroid scans, is likely to be clinically relevant if complemented by additional studies with different variables in patients with thyroid disease.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1680-1681
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• 2011

In this paper, particle counting system using a CMOS image sensor is demonstrated. The system utilizes a linear photodetector array as a detection element. Therefore, the particles are detected by large detection region, in contrast to a single detector in conventional particle counting devices, while maintaining the sensitivity. The advantage of proposed system is that particles are detected in a relatively large area without using the particle focusing method. Also, proposed system can be easily integrated with a microfluidic chip by attaching the device underneath the bottom plate of the microfluidic chip. Detection of polystyrene microbeads has been tested at a flow rate of 4.89mm/s. For 21 measurements, proposed system showed an average count error of 7.29% and a standard deviation of 4.74%. Potentially, the proposed system can detect even smaller particles simply by utilizing a higher resolution CMOS image sensor.