• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.4
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• pp.404-409
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• 2004

We fabricated photo-sensor for fluorescence detection in LOC. LOC is high throughput screening system. Our LOC screens biochemical reaction of protein using the immunoassay, and converts biochemical reaction into electrical signal using LIF(Laser Induced Fluorescence) detection method. Protein is labeled with rhodamine intercalating dye and finger PIN photodiode is used as photo-sensor We measured fluorescence emission of rhodamine dye and analyzed tendency of fluorescence detection, according to photo-sensor size, light intensity, and rhodamine concentration. Detection current was almost linearly proportional to two parameters, intensity and concentration, and was inversely proportional to photo-sensor size. Integrated LOC consists of optical-filter deposited photo-sensor and PDMS microchannel detected 50 (pg/${mu}ell$) rhodamine. For integrated LOC including light source, we used green LED as the light source and measured emitted fluorescence.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.439-443
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• 2008

It is shown that even if the modulating frequency of the light is too high for direct detection the signal can be extracted by frequency conversion at the same time as the detection by means of the nonlinearity of the APD. When this frequency conversion detection is applied to an optical receiver, the detection bandwidth can be increased while the configuration of the optical detection circuit and the signal processing in the subsequent stages are simplified. A fundamental analysis is carried out with an APD which is confirmed experimentally.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.579-583
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• 2012

We have designed the small particle detection system. The scatteing effect of light was used to detect small particle. The fabricated system consisted of laser diode, lens, pin hole, and photo detector. The aperture, lens, and photo detector were optimized to improve the performance of detection system. The fabricated detection system detected the scattered light by small particle entering into detection system and its response time was fast.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.347-359
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• 2010

Ortho-photos provide valuable spatial and spectral information for various Geographic Information System (GIS) and mapping applications. The absence of relief displacement and the uniform scale in ortho-photos enable interested users to measure distances, compute areas, derive geographic locations, and quantify changes. Differential rectification has traditionally been used for ortho-photo generation. However, differential rectification produces serious problems (in the form of ghost images) when dealing with large scale imagery over urban areas. To avoid these artifacts, true ortho-photo generation techniques have been devised to remove ghost images through visibility analysis and occlusion detection. So far, the Z-buffer method has been one of the most popular methods for true ortho-photo generation. However, it is quite sensitive to the relationship between the cell size of the Digital Surface Model (DSM) and the Ground Sampling Distance (GSD) of the imaging sensor. Another critical issue of true ortho-photo generation using high resolution satellite imagery is the scan line search. In other words, the perspective center corresponding to each ground point should be identified since we are dealing with a line camera. This paper introduces alternative methodology for true ortho-photo generation that circumvents the drawbacks of the Z-buffer technique and the existing scan line search methods. The experiments using real data are carried out while comparing the performance of the proposed and the existing methods through qualitative and quantitative evaluations and computational efficiency. The experimental analysis proved that the proposed method provided the best success ratio of the occlusion detection and had reasonable processing time compared to all other true ortho-photo generation methods tested in this paper.

• Proceedings of the Optical Society of Korea Conference
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• 2002.11a
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• pp.246-247
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• 2002

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.108-113
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• 2009

Significant attention has recently been drawn to digital home photo albums that use face detection technology. The tendency can be found in home photo albums that people prefer to allocate concerned objects in the center of the image rather than the boundary when they take a picture. To improve detection performance and speed that are important factors of face detection task, this paper proposes a face detection method that takes spatial context information into consideration. Experiments were performed to verify the usefulness of the proposed method and results indicate that the proposed face detection method can efficiently reduce the false positive rate as well as the runtime of face detection.

• Journal of KIISE
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• v.43 no.12
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• pp.1356-1364
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• 2016

This paper proposes a novel aesthetic photo recomposition method using a deep convolutional neural network (DCNN). Previous recomposition approaches define the aesthetic score of photo composition based on the distribution of salient objects, and enhance the photo composition by maximizing the score. These methods suffer from heavy computational overheads, and often fail to enhance the composition because their optimization depends on the performance of existing salient object detection algorithms. Unlike previous approaches, we address the photo recomposition problem by utilizing DCNN, which shows remarkable performance in object detection and recognition. DCNN is used to iteratively predict cropping directions for a given photo, thus generating an aesthetically enhanced photo in terms of composition. Experimental results and user study show that the proposed framework can automatically crop the photo to follow specific composition guidelines, such as the rule of thirds.

• ETRI Journal
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• v.30 no.3
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• pp.432-440
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• 2008

In this paper, a user-friendly mobile photo album system and albuming functions to support it are introduced. Stand-alone implementation in a mobile device is considered. The main idea of user-friendly photo browsing for albuming functions is to enable users to organize and browse their photos along semantically meaningful axes of events, personal identities, and categories. Experimental results demonstrate that the proposed method would be sufficiently useful and efficient for browsing personal photos in mobile environment.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.2
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• pp.100-105
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• 2022

This paper applies the arc detection algorithm to prevent the false detection in photo voltaic series arc detection circuit, which is required not only to detect the series arc quickly, but also not falsely detect the arc for the non-arc noise. For this purpose, this study proposes a rapid and preventive false detection method of single peak noise and short noise signals. First, to prevent false detection by single peak noise, Discrete wavelet transform (DWT)-based characteristic parameters are applied to determine the shape and the amplitude of the noise. In addition, arc fault detection within a few milliseconds is performed with the DWT iterative algorithm to quickly prevent false detection for short noise signals, considering the continuity of serial arc noise. Thus, the method operates not only to detect series arc, but also to avoid false arc detection for peak and short noises. The proposed algorithm is applied to real-time serial arc detection circuit based on the TMS320F28335 DSP. The serial arc detection and peak noise filtering performances are verified in the built simulated arc test facility. Furthermore, the filtering performance of short noise generated through DC switch operation is confirmed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.15-19
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• 2002

Automatic detection of interstitial lung disease using Neural Network is presented. The rounded opacities in the pneumoconiosis X-ray photo are picked up quickly by a back propagation (BP) neural network with several typical training patterns. The training patterns from 0.6 mm ${\O}$ to 4.0 mm ${\O}$ are made by simple circles. The total evaluation is done from the size and figure categorization. Mary simulation examples show that the proposed method gives much reliable result than traditional ones.