• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1081-1088
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• 2013

Hyperspectral cameras acquire reflectance values at many different wavelength bands. Dimensions tend to increase because spectral information is stored in each pixel. Several attempts have been made to reduce dimensional problems such as the feature selection using Adaboost and dimension reduction using the Simulated Annealing technique. We propose a novel material detection method that consists of four steps: feature band selection, feature extraction, SVM (Support Vector Machine) learning, and target and specific region detection. It is a combination of the band ratio method and Simulated Annealing algorithm based on detection rate. The experimental results validate the effectiveness of the proposed feature selection and band ratio method.

• Journal of Korea Multimedia Society
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• v.25 no.7
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• pp.903-911
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• 2022

A shrimp quality detection model using YOLOv4 deep learning algorithm is designed, which is superior in terms of network architecture, data processing and feature extraction. The shrimp images were taken and data expanded on their own, the LableImage platform was used for data annotation, and the network model was trained under the Darknet framework. Through comparison, the final performance of the model was all higher than other common target detection models, and its detection accuracy reached 93.7% with an average detection time of 47 ms, indicating that the method can effectively detect the quality of shrimp in the production process.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.8
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• pp.661-669
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• 2017

This paper describes an MMTI(Maritime Moving Target Indicator) for periscope detection in airborne radar. Firstly, we analyze the characteristics of sea clutter, sea targets. Secondly, we study the differences between GMTI(Ground Moving Target Indicator) and MMTI. This paper proposes an optimal MMTI operating environment and method. We also suggest a signal processing algorithm using STAP(Space-Time Adaptive Processing) for detecting small RCS target moving low speed. The detection probability for moving target with MDV(Minimum Detectable Velocity) is simulated under various RCS and multi-channel system. Finally, we analyze the major performance for range, velocity and azimuth accuracy.

• Food Science of Animal Resources
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• v.34 no.5
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• pp.717-723
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• 2014

A rapid and specific PCR assay for the simultaneous detection of Listeria monocytogenes, Escherichia coli O157:H7, Bacillus cereus, Salmonella spp., and Staphylococcus aureus in foods was developed to reduce the detection time and to increase sensitivity. Multiplex PCR developed in this study produced only actA, fliC, hbl, invA, ileS amplicons, but did not produce any non-specific amplicon. The primer sets successfully amplified the target genes in the multiplex PCR without any non-specific or additional bands on the other strains. The multiplex PCR assays also amplified some target genes from five pathogens, and multiplex amplification was obtained from as little as 1 pg of DNA. According to the results from the sensitivity evaluation, the multiplex PCR developed in this study detected 10 cells/mL of the pathogens inoculated in milk samples, respectively. The results suggested that multiplex PCR was an effective assay demonstrating high specificity for the simultaneous detection of five target pathogens in food system.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1839-1845
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• 2016

Detecting remote targets is important to active protection system (APS) or infrared search and track (IRST) applications. In normal situation, the well-known constant false alarm rate (CFAR) detector works properly. However, decoys in APS or closely spaced targets in IRST degrade the detection capability by increasing background noise level in the CFAR detector. This paper presents a context aware CFAR detector by the intensity sorting and selection of background region to reduce the effect of neighboring targets that lead to incorrect estimation of background statistics. The existence of neighboring targets can be recognized by intensity sorting where neighboring targets usually show highest ranks. The proposed background statistics (mean, standard deviation) estimation method from median local pixels can be aware of the background context and reduce the effects of the neighboring targets, which increase the signal-to-clutter ratio. The experimental results on the synthetic APS sequence, real adjacent target sequence, and remote pedestrian sequence validated that the proposed method produced an enhanced detection rate with the same false alarm rate compared with the hysteresis-CFAR (H-CFAR) detection.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.43-53
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• 2012

In the this paper, a gesture-based user interface based on object detection using predefined gesture and the tracking of the detected object is proposed. For object detection, moving objects in a frame are computed by comparing multiple previous frames and predefined gesture is used to detect the target object among those moving objects. Any object with the predefined gesture can be used to control. We also propose an object tracking algorithm, namely density based meanshift algorithm, that uses color distribution of the target objects. The proposed object tracking algorithm tracks a target object crossing the background with a similar color more accurately than existing techniques. Experimental results show that the proposed object detection and tracking algorithms achieve higher detection capability with less computational complexity.

• Bulletin of the Korean Chemical Society
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• v.31 no.11
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• pp.3099-3102
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• 2010

A label-free DNA detection method was developed for a simple electrochemical DNA sensor with a short assay time. Self-assembled monolayers of peptide nucleic acid were used as a probe on gold electrodes. The formation of the self-assembled monolayers on the gold electrodes was successfully checked by means of cyclic voltammetry. The target DNA, hybridized with peptide nucleic acid, can be detected by the anodic peak current of ferrocene dendrimers, which interact electrostatically with the target DNA. This anodic peak current was measured by square wave voltammetry at 0.3 V to decrease the detection limit on the order of the nanomolar concentrations. As a result, the label-free electrochemical DNA sensor can detect the target DNA in concentrations ranging from 1 nM to $1\;{\mu}M$ with a detection limit of 1 nM.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.276-276
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• 2013

Here we report an integrated microdevice consisting of an efficient passive mixer, a magnetic separation chamber, and a capillary electrophoretic microchannel in which DNA barcode assay, target pathogen separation, and barcode DNA capillary electrophoretic analysis were performed sequentially within 30 min for multiplex pathogen detection at the single-cell level. The intestine-shaped serpentine 3D micromixer provides a high mixing rate to generate magnetic particle-pathogenic bacteria-DNA barcode labelled AuNP complexes quantitatively. After magnetic separation and purification of those complexes, the barcode DNA strands were released and analyzed by the microfluidic capillary electrophoresis within 5 min. The size of the barcode DNA strand was controlled depending on the target bacteria (Staphylococcus aureus, Escherichia coli O157:H7, and Salmonella typhimurium), and the different elution time of the barcode DNA peak in the electropherogram allows us to recognize the target pathogen with ease in the monoplex as well as in the multiplex analysis. In addition, the quantity of the DNA barcode strand (~104) per AuNP is enough to be observed in the laser-induced confocal fluorescence detector, thereby making single-cell analysis possible. This novel integrated microdevice enables us to perform rapid, sensitive, and multiplex pathogen detection with sample-in-answer-out capability to be applied for biosafety testing, environmental screening, and clinical trials.

• The Plant Pathology Journal
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• v.37 no.3
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• pp.291-298
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• 2021

False smut caused by Ustilaginoidea virens is an important rice fungal disease that significantly decreases its production. In the recent past, conventional methods have been developed for its detection that is time-consuming and need high-cost equipments. The research and development in nanotechnology have made it possible to assemble efficient recognition interfaces in biosensors. In this study, we present a simple, sensitive, and selective oxidized graphene-based geno-biosensor for the detection of rice false smut. The biosensor has been developed using a probe DNA as a biological recognition element on paper electrodes, and oxidized graphene to enhance the limit of detection and sensitivity of the sensor. Probe single-stranded DNA (ssDNA) and target ssDNA hybridization on the interface surface has been quantitatively measured with the electrochemical analysis tools namely, cyclic voltammetry, and linear sweep voltammetry. To confirm the selectivity of the device, probe hybridization with non-complementary ssDNA target has been studied. In our study, the developed sensor was able to detect up to 10 fM of target ssDNA. The paper electrodes were employed to produce an effective and cost-effective platform for the immobilization of the DNA and can be extended to design low-cost biosensors for the detection of the other plant pathogens.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.505-508
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• 2000

The success of target reconstruction in SAR(Synthetic Aperture Radar) imaging system is greatly dependent on the coherent detection. Primary causes of incoherent detection are uncompensated target or sensor motion, random turbulence in propagation media, wrong path in radar platform, and etc. And these appear as multiplicative phase error to the echoed signal, which consequently, causes fatal degradations such as fading or dislocation of target image. In this paper, we present iterative phase error estimation scheme which uses echoed data in all temporal frequencies. We started with analyzing wave equation for one point target and extend to overall echoed data from the target scene - The two wave equations governing the SAR signal at two temporal frequencies of the radar signal are combined to derive a method to reconstruct the complex phase error function. Eventually, this operation attains phase error correction algorithm from the total received SAR signal. We verify the success of the proposed algorithm by applying it to the simulated spotlight-mode SAR data.