• Analytical Science and Technology
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• v.24 no.1
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• pp.51-59
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• 2011

Genetic Identification has become an important forensic investigation method which discerns identity through analysis of physical samples discovered in various crime scenes. Recently more samples are being requested to undergo A-STR analysis of low copy number (LCN) DNA, which is known as touch evidence-type sample and left on various objects such as a pen briefly used by the criminal, the gear of the car used for driving, the handle, and various buttons inside a car. This research attempted to extract the LCN DNA of the touch evidencetype left on crushed fingerprints on firearms, etc. and examine the genotyping success rate. Four types of firearms (M16, K1A, COLT 45 Pistol, M29 Revolver) were fired individually and physical samples were gathered from four parts of each firearm. Subsequently, in order to extract the LCN DNA, Microkit and $Prepfiler^{TM}$ were used to compare and analyze the quantity of DNA extracted and the genotyping success rate. Analysis results showed that the quantity of DNA extracted by $Prepfiler^{TM}$ was on average 1.7 times higher than that of Microkit, and in genotype analysis success rate $Prepfiler^{TM}$ also demonstrated 24.9% on average in contrast to 0% for Microkit. In regards to the grip part of the K1A, $Prepfiler^{TM}$'s success rate was as high as 50.6%.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.453-462
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• 2021

A lot of license plate data is required for car number recognition. License plate data needs to be balanced from past license plates to the latest license plates. However, it is difficult to obtain data from the actual past license plate to the latest ones. In order to solve this problem, a license plate recognition study through deep learning is being conducted by creating a synthetic license plates. Since the synthetic data have differences from real data, and various data augmentation techniques are used to solve these problems. Existing data augmentation simply used methods such as brightness, rotation, affine transformation, blur, and noise. In this paper, we apply a style transformation method that transforms synthetic data into real-world data styles with data augmentation methods. In addition, real license plate data are noisy when it is captured from a distance and under the dark environment. If we simply recognize characters with input data, chances of misrecognition are high. To improve character recognition, in this paper, we applied the DeblurGANv2 method as a quality improvement method for character recognition, increasing the accuracy of license plate recognition. The method of deep learning for license plate detection and license plate number recognition used YOLO-V5. To determine the performance of the synthetic license plate data, we construct a test set by collecting our own secured license plates. License plate detection without style conversion recorded 0.614 mAP. As a result of applying the style transformation, we confirm that the license plate detection performance was improved by recording 0.679mAP. In addition, the successul detection rate without image enhancement was 0.872, and the detection rate was 0.915 after image enhancement, confirming that the performance improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.837-839
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• 2012

When the for occurred, the driver does not get the vision is has difficult on driving. In this case, the probability of occurrence of accidents are very high level. To reduce accidents, this system provide drivers with the safety of ensure to measures that a service inform current situation. in this paper, the crash occur in fog to prevent accident using vehicle safety system to give a alarm and control. The proposed system is installed on the outside of the vehicle, humidity, and ambient light sensors inside the car from the information collected by the system controller for the detection of fog conditions using video equipment and then finally the fog occurs if you do not get the driver's field of events is causing the system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.78-88
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• 2012

AVIs on the road are installed for (1) security (2) and for traffic, and they are various managed by (1) police department, (2) local government, (3) national highway management, (4) Korean highway corporation. But although the collected data of the plate number, the travel time, the picture of the car are same, they are used in purposes of its installation because the managements are different and the data are difficult to be connected with each other. For this reason, this study is to appraise the application for creating traffic information by integrating these data, and to suggest the introduction of spatial detection system which integrated security-traffic AVI DB for the purpose of reliability improvement of center's velocity. The estimating sections of link travel information seems to be expanded, and the error rate between the center's velocity and the experimental value will be reduced if integrated DB of traffic and security AVIs is used for creating traffic information. Also, the crime prevention and arrest rate is expected to rise in the future.

• Food Science of Animal Resources
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• v.30 no.1
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• pp.73-86
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• 2010

The current study was designed to optimize solid phase microextraction (SPME)-GC-MS conditions for extraction and analysis of volatile components for Hanwoo beef and to establish a tentative database of flavor components. Samples were taken from Hanwoo longissimus muscle (30 mon old steer, $1^+B$ carcass grade) at 24 h postmortem. Results indicated that the optimum adsorption time for $75{\mu}m$ CAR/PDMS fiber was 60 min at $60^{\circ}C$. Thermal cleaning at $250^{\circ}C$ for 60 min was the best practice for decontamination of the fiber. A short analysis program with a sharp oven temperature ramp resulted in a better resolution and higher number of measurable volatile components. With these conditions, 96 volatile compounds were identified with little variation including 22 aldehydes, 8 ketones, 31 hydrocarbons, 12 alcohols, 8 nitrogen- and sulfurcontaining compounds, 5 pyrazines and 10 furans. A noticeable observation was the high number of hydrocarbons, aldehydes, ketones, alcohols and 2-alkylfurans which were generated from lipid decomposition especially the oxidation and degradation of unsaturated and saturate fatty acids. This implies that these compounds can be candidates for flavor specification of highly marbled beef such as Hanwoo flavor.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.133.1-133
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• 2003

Gummy stem blight, caused by Didymella bryoniae occurs exclusively on cucurbits. This fungus has been known not to produce its pycnidium in vitro unless irradiated. Through this study, we optimized cultural conditions for mass-production of pycnidiospore by Metal Halide Lamp irradiation. In brief, the mycelial was cultured at $26^{\circ}C$ on PDA, for 2 days under the darkness, and then the plate was illuminated with MH lamp continuously for 3-4 days at $26^{\circ}C$, a great number of pycnidia was simultaneously formed. Thus produced pycnidiospores were used as immunogen. From fusions of myeloma cell (v-653) with splenocytes from immunifed mice were car ried out. And, two hybridoma cell lines that recognized the immunogen Didymella bryoniae were obtained. One Monoclonal Antibody, Db1, recognized the supernatant and the other monoclonal antibody, Db15, recognized the spore. Two clones were selected which were used to produce ascite fluid two MAb Db1 and Db15, were immunotyped and identified as IgG1 and IgG2b, respectively. Titer of MAb Db1 and MAb Db15 was measured absorbance exceeded 0.5 even at a $10^{-5}$ dilution. The MAbs reacted positively with Didymella bryoniae but none reacted with other of fungi and CMV, CGMMV Sensitivity of MAb was precise enough to detect spore concentration as low as $10^{3}$ well by indirect ELISA characterization of the MAb Db1, Db15 antigen by heat and protease treatments show that the epitope recognized by the MAb Bb1, Db15 were a glycoprotein.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.957-964
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• 2011

The image stabilization is the procedure of stabilizing the blurred image with image processing method. Due to easy detection of global motion, PA(Projection algorithm) based on digital image stabilization has been studied by many researchers. PA has the advantage of easy implementation and low complexity, but in the case of serious rotational motion the accuracy of the algorithm will be cut down because of its fixed exploring range, and, on the other hand, if extending the exploring range, the block for detecting motion will become small, then we cannot detect correct global motion. In this paper, to overcome the drawback of conventional PA, an Iterative Projection Algorithm (IPA) is proposed, which improved the correctness of global motion by detecting global motion with detecting block which is appropriate to different extent of motion. With IPA, in the case of processing 1000 continual frames shot in automobile, compared with conventional algorithm and other detecting range, the results of PSNR is improved 6.8% at least, and 28.9% at the most.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.655-661
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• 2017

It is a very important task to extract character regions contained in various input color images, because characters can provide significant information representing the content of an image. In this paper, we propose a new method for extracting character regions from various input images using MCT features and an AdaBoost algorithm. Using geometric features, the method extracts actual character regions by filtering out non-character regions from among candidate regions. Experimental results show that the suggested algorithm accurately extracts character regions from input images. We expect the suggested algorithm will be useful in multimedia and image processing-related applications, such as store signboard detection and car license plate recognition.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.63-72
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• 2007

The traffic sign on the road should be easy to distinguishable even from far, and should be recognized in a short time. As traffic sign is a very important object which provides important information for the drivers to enhance safety, it has to attract human's attention among any other objects on the road. This paper proposes a new method of detecting the area of traffic sign, which uses attention module on the assumption that we attention our gaze on the traffic sign at first among other objects when we drive a car. In this paper, we analyze the previous studies of psycophysical and physiological results to get what kind of features are used in the process of human's object recognition, especially color processing, and with these results we detected the area of traffic sign. Various kinds of traffic sign images were tested, and the results showed good quality(average 97.8% success).

• Korean Journal of Cognitive Science
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• v.25 no.1
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• pp.51-71
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• 2014

This paper presents an image enhancement method in real road traffic scenes. The images captured by the camera on the car cannot keep the color constancy as illumination or weather changes. In the real environment, these problems are more worse at back light conditions and at night that make more difficult to the applications of the vision-based intelligent vehicles. Using the existing image enhancement methods without considering the position and intensity of the light source and their geometric relations the image quality can even be deteriorated. Thus, this paper presents a fast and effective method for image enhancement resembling human cognitive system which consists of 1) image preprocessing, 2) color-contrast evaluation, 3) alpha blending of over/under estimated image and preprocessed image. An input image is first preprocessed by gamma correction, and then enhanced by an Automatic Color Enhancement(ACE) method. Finally, the preprocessed image and the ACE image are blended to improve image visibility. The proposed method shows drastically enhanced results visually, and improves the performance in traffic sign detection of the vision based intelligent vehicle applications.