• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.38-43
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• 2008

Skin color information is an important feature for face region detection in color images. This can detect face region using statistical skin color model who is created from skin color information. However, due to the including of different race of people's skin color points, this general statistical model is not accurate enough to detect each specific image as we expected. This paper proposes method to detect correctly face region in various color image that other complexion part is included. In this method set face candidate region applying complexion Gausian distribution based on YCbCr skin color model and applied mathematical morphology to remove noise part and part except face region in color image. And achieved correct face region detection because using Haar-like feature. This approach is capable to distinguish face region from extremely similar skin colors, such as neck skin color or am skin color. Experimental results show that our method can effectively improve face detection results.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.155-160
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• 2014

In this paper, an algorithm using RGB-depth camera is proposed to detect smoke in interrior. RGB-depth camera, the Kinect provides RGB color image and depth information. The Kinect sensor consists of an infra-red laser emitter, infra-red camera and an RGB camera. A specific pattern of speckles radiated from the laser source is projected onto the scene. This pattern is captured by the infra-red camera and is analyzed to get depth information. The distance of each speckle of the specific pattern is measured and the depth of object is estimated. As the depth of object is highly changed, the depth of object plain can not be determined by the Kinect. The depth of smoke can not be determined too because the density of smoke is changed with constant frequency and intensity of infra-red image is varied between each pixels. In this paper, a smoke detection algorithm using characteristics of the Kinect is proposed. The region that the depth information is not determined sets the candidate region of smoke. If the intensity of the candidate region of color image is larger than a threshold, the region is confirmed as smoke region. As results of simulations, it is shown that the proposed method is effective to detect smoke in interior.

• Food Science and Biotechnology
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• v.15 no.4
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• pp.625-630
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• 2006

Polymerase chain reaction (PCR) method was developed for the specific detection of insect-resistant rice containing cry1Ac gene derived from Bacillus thuringiensis (Bt). Primers were designed from the 35S promoter, NOS terminator, cry1Ac gene, and sucrose phosphate synthase (SPS) for general screening of Bt rice. By sequencing the PCR products from the two putative kinds of Bt rice, we designed a specific primer from the junction region between the cry1Ac gene and the NOS terminator that had been inserted into Bt rice. The construct-specific primer was employed to amplify a 147 bp product in the two lines of Bt rice. No amplified products were observed from the other Bt crops with various Bt genes introduced. In qualitative PCR analysis, the limit of detection was 0.005 ng from genomic DNA of Bt rice. In addition, PCR analysis was performed on 64 kinds of rice presently available in the Korean market, and no Bt rice was detected. This method presented in this paper can be used as a highly sensitive and specific detection method of Bt rice.

• Mycobiology
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• v.41 no.2
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• pp.86-93
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• 2013

Sequence characterized amplified region (SCAR) markers are one of the most effective and accurate tools for microbial identification. In this study, we applied SCAR markers for the rapid and accurate detection of Phytophthora katsurae, the casual agent of chestnut ink disease in Korea. In this study, we developed seven SCAR markers specific to P. katsurae using random amplified polymorphic DNA (RAPD), and assessed the potential of the SCAR markers to serve as tools for identifying P. katsurae. Seven primer pairs (SOPC 1F/SOPC 1R, SOPC 1-1F/SOPC 1-1R, SOPC 3F/SOPC 3R, SOPC 4F/SOPC 4R, SOPC 4F/SOPC 4-1R, SOPD 9F/SOPD 9R, and SOPD 10F/SOPD 10R) from a sequence derived from RAPD fragments were designed for the analysis of the SCAR markers. To evaluate the specificity and sensitivity of the SCAR markers, the genomic DNA of P. katsurae was serially diluted 10-fold to final concentrations from 1 mg/mL to 1 pg/mL. The limit of detection using the SCAR markers ranged from $100{\mu}g/mL$ to 100 ng/mL. To identify the limit for detecting P. katsurae zoospores, each suspension of zoospores was serially diluted 10-fold to final concentrations from $10{\times}10^5$ to $10{\times}10^1$ zoospores/mL, and then extracted. The limit of detection by SCAR markers was approximately $10{\times}10^1$ zoospores/mL. PCR detection with SCAR markers was specific for P. katsurae, and did not produce any P. katsurae-specific PCR amplicons from 16 other Phytophthora species used as controls. This study shows that SCAR markers are a useful tool for the rapid and effective detection of P. katsurae.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.6
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• pp.891-895
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• 2019

Objective: Aim of present study was the set up of a fast and reliable protocol using species-specific markers for the quali-quantitative analysis of DNA and the detection of ruminant biological components in dairy products. For this purpose, the promoter of the gene coding for the ${\alpha}$-lactoalbumin (LALBA) was chosen as possible candidate for the presence of short interspersed nuclear elements (SINEs). Methods: DNA was isolated from somatic cells of 120 individual milk samples of cattle (30), Mediterranean river buffalo (30), goat (30), and sheep (30) and the gene promoter region (about 600/700 bp) of LALBA (from about 600 bp upstream of exon 1) has been sequenced. For the development of a single polymerase chain reaction (PCR) protocol that allows the simultaneous identification of DNA from the four species of ruminants, the following internal primers pair were used: 5'-CACTGATCTTAAAGCTCAGGTT-3' (forward) and 5'-TCAGA GTAGGCCACAGAAG-3' (reverse). Results: Sequencing results of LALBA gene promoter region confirmed the presence of SINEs as monomorphic "within" and variable in size "among" the selected species. Amplicon lengths were 582 bp in cattle, 592 bp in buffalo, 655 in goat and 729 bp in sheep. PCR specificity was demonstrated by the detection of trace amounts of species-specific DNA from mixed sources ($0.25ng/{\mu}L$). Conclusion: We developed a rapid PCR protocol for the quali-quantitative analysis of DNA and the traceability of dairy products using a species-specific marker with only one pair of primers. Our results validate the proposed technique as a suitable tool for a simple and inexpensive (economic) detection of animal origin components in foodstuffs.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.575-578
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• 1999

The principal features of a face are as follows : skin-tone, symmetry, and requisites such as shape of ellipse, eyes, nose, mouth. Also, faces have different size, various shape and position. In case of application of face recognition and detection without preprocessing, efficiency of the performance is decreased. In addition, face itself, complex background, image quality, etc. are included. Therefore, previous face recognition methods are implemented on the base of specific constraints of the face image. In this paper, we propose the efficient and automatic face detection algorithm for minimizing influence such as complex background, image quality, etc. This face detection technique consists of skin-tone, candidate face region and face region extractions.

• Journal of Sensor Science and Technology
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• v.24 no.1
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• pp.1-5
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• 2015

The V-grooved single-mode fiber in which a surface part of the core was removed was investigated as a quasi-distributed water detection sensor. In the normal state, the V-grooved region is filled and covered with a specific RI (Refractive Index)-matched medium, and the sensor experiences minimal optical loss. As water invades the V-grooved region, the material is dissolved and removed, and a considerable optical loss occurs owing to the large RI difference between the fiber core and water. The experimental results showed the feasibility of the device as a sensor element of the quasi-distributed water detection sensor system based on general optical time domain reflectometry (OTDR).

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.641-648
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• 2001

A face detection in color images is important for many multimedia applications. It is first step for face recognition and can be used for classifying specific shorts. This paper describes a new method to detect faces in color images based on the skin color and hair color. This paper presents a fuzzy-based method for classifying skin color region in a complex background under varying illumination. The Fuzzy rule bases of the fuzzy system are generated using training method like a genetic algorithm(GA). We find the skin color region and hair color region using the fuzzy system and apply the convex-hull to each region and find the face from their intersection relationship. To validity the effectiveness of the proposed method, we make experiment with various cases.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.393-400
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• 2013

Hand shape recognition is a fundamental technique for implementing natural human-computer interaction. In this paper, we discuss a method for effectively detecting a hand region in Kinect-based hand shape recognition. Since Kinect is a camera that can capture color images and infrared images (or depth images) together, both images can be exploited for the process of detecting a hand region. That is, a hand region can be detected by finding pixels having skin colors or by finding pixels having a specific depth. Therefore, after analyzing the performance of each, we need a method of properly combining both to clearly extract the silhouette of hand region. This is because the hand shape recognition rate depends on the fineness of detected silhouette. Finally, through comparison of hand shape recognition rates resulted from different hand region detection methods in general environments, we propose a high-performance hand region detection method.

• Research in Plant Disease
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• v.30 no.3
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• pp.304-311
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• 2024

There are concerns about the introduction and spread of plant pests and pathogens with globalization and climate change. As commercial control agents have not been developed for plant viruses, it is important to prevent virus spread. In this study, we developed a multiplex polymerase chain reaction (PCR) detection method to rapidly diagnose and control three DNA (papaya golden mosaic virus, Lindernia anagallis yellow vein virus, and melon chlorotic leaf curl virus) and two RNA (papaya leaf distortion mosaic virus and lettuce chlorosis virus) viruses that infect papaya. Specific primer sets were designed for the virus coat protein. Performing PCR, clear bands were observed with no non-specific reaction. Our multiplex PCR method can simultaneously detect small amounts of DNA/RNA to diagnose five viruses infecting papaya and prevent the spread of the virus.