• Analytical Science and Technology
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• v.37 no.3
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• pp.189-199
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• 2024

In forensic genetics, when it is not possible to confirm an individual's identity through STR profile analysis, additional information about the individual can be obtained using DNA-based phenotypic traits estimation. Recently, various researches have been conducted on methods to determine externally visible characteristics (EVC) such as eyes, hair, and skin color. However, relying solely on such phenotypic traits information has limitations for application in East Asian regions, including Korea. In this study, in order to utilize EVC related to an individual's appearance as investigative information, SNPs related to eye shape, hair thickness, skin color, as well as baldness, body type, high myopia, facial shape, acne, and behavioral habits were explored. A total of 50 SNPs were selected, and a targeted amplicon NGS panel capable of amplifying them all at once was developed. Experimental results confirmed the allelic types and frequencies of the 50 SNPs in 14 samples. We plan to use this panel to investigate the correlation between genotype and phenotype using various samples, and to develop methods for interpreting the results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.793-800
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• 2004

In this paper, we propose a new automatic pipe grading algorithm for an efficient management of transmission pipe under the ground. Since the conventional transmission pipe evaluation was conducted by subjective decision made by an individual operator, it was difficult to grade them by means of numerical methods and also hard to realistically construct numerical database system. To solve these problems, we Int obtain some information on the current condition of pipes' sections by shooting laser beam at a regular rate and then apply grading algorithm after complete calculation of minimum diameter of pipe. We use some of preprocessing techniques to reduce noise and also use various color models to consider special conditions of each inner pipe. The measurement of pipes' minimum diameter and decision of grade are performed through a detailed processing stages. By some experimental results performed in the field, we show that over 90 percent of correct grade decisions are made by the proposed algorithm.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.430-439
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• 2015

The demand of violence detection techniques using a video analysis to help prevent crimes is increasing recently. Many researchers have studied vision based behavior recognition but, violent behavior analysis techniques usually focus on violent scenes in television and movie content. Many methods previously published usually used both a color(e.g., skin and blood) and motion information for detecting violent scenes because violences usually involve blood scenes in movies. However, color information (e.g., blood scenes) may not be useful cues for violence detection in surveillance videos, because they are rarely taken in real world situations. In this paper, we propose a method of violent behavior detection in surveillance videos using motion vectors such as flow vector magnitudes and changes in direction except the color information. In order to evaluate the proposed algorithm, we test both USI dataset and various real world surveillance videos from YouTube.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.152-157
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• 2010

The development of computer and internet has introduced various types of media - such as, image, audio, video, and voice - to the traditional text-based information. However, most of the information retrieval systems are based only on text, which results in the absence of ability to use available information. By utilizing the available media, one can improve the performance of search system, which is commonly called content-based retrieval and content-based image retrieval system specifically tries to incorporate the analysis of images into search systems. In this paper, a content-based image retrieval system using HSI color space, ART2 algorithm, and SOM algorithm is introduced. First, images are analyzed in the HSI color space to generate several sets of features describing the images and an SOM algorithm is used to provide candidates of training features to a user. The features that are selected by a user are fed to the training part of a search system, which uses an ART2 algorithm. The proposed system can handle the case in which an image belongs to several groups and showed better performance than other systems.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.153-154
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• 2008

Digital photographic analysis is currently considered as a routine procedure in clinic because periodic follow-up examinations can provide meaningful information for diagnosis. However, it is impractical to separately evaluate all suspicious lesions with conventional digital photographic systems, which have inconsistent characteristics of the environmental conditions. To address the issue, it is necessary for total diagnostic evaluation in clinic to integrate conventional systems. Previously, a multimodal digital photographic imaging system, which provides a conventional color image, parallel and cross polarization color images and a fluorescent color image, was developed for objective evaluation of facial skin lesions. Based on our previous study, we introduce a commercial product, "DermaVision-PRO," for routine use in clinical application in dermatology. We characterize the system and describe the image analysis methods for objective evaluation of skin lesions. In order to demonstrate the validity of the system in dermatology, sample images were obtained from subjects with various skin disorders, and image analysis methods were applied for objective evaluation of those lesions.

• Journal of Korea Game Society
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• v.20 no.1
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• pp.3-12
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• 2020

This paper proposes a structure based on a production method of concept art focused on the player's experience through a module by using the game aesthetics of the MDA framework. And also a partially automated process established in concept art production by using the 'Adobe Color image color extraction' as a tool in the work production process. This paper proposed a work process of not just a personal expression but a systematic molding expression to use, and this could see as the various possibilities of game concept art productions.

• Journal of Information Display
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• v.11 no.1
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• pp.17-20
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• 2010

With the increasing demand for a better FPD image quality, better evaluation metrics and advanced display quality measurement methods are required to meet these needs. There are many measurement methods for evaluating the viewing angle of various display devices, but these methods, which include luminance drop, color shift, and contrast ratio decrease, are imperfect considering that human perception does not completely correlate to them. In this paper, a new method of measuring the perceptual angle of FPDs is proposed, considering human visual perception, which uses the color space of the color appearance model.

• Journal of Korean Society of Water and Wastewater
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• v.21 no.6
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• pp.663-670
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• 2007

This study was performed to provide basic information for evaluating the efficiency and applicable extent of photocatalysis and ozonation for the treatment of dye wastewater. The treatability of dye wastewater by $UV/TiO_2$ and $UV/TiO_2/O_3$ advanced oxidation process (AOP) was investigated under various conditions. The experiments were conducted in a batch reactor of 50 liters equipped with twelve UV Lamps of 16W. In $UV/TiO_2$ AOP, the removal efficiency of TCODMn and Color increased to 58% and 67% respectively with increasing UV intensity. Also, The removal efficiency of TCODMn and Color increased to 97% and 99% respectively with increasing $H_2O_2$. Acid area was more efficient than neutral and alkalic areas in wastewater treatment, and pH 5 was the most effective and the treatment efficiency continually increased as the amount of photocatalyst was increased. When the photocatalyst was increased, TCODMn was removed faster than Color.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.420-438
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• 2004

Artificially or naturally contained texts in the natural images have significant and detailed information about the scenes. If we develop a method that can extract and recognize those texts in real-time, the method can be applied to many important applications. In this paper, we suggest a new method that extracts the text areas in the natural images using the low-level image features of color continuity. gray-level variation and color valiance and that verifies the extracted candidate regions by using the high-level text feature such as stroke. And the two level features are combined hierarchically. The color continuity is used since most of the characters in the same text lesion have the same color, and the gray-level variation is used since the text strokes are distinctive in their gray-values to the background. Also, the color variance is used since the text strokes are distinctive in their gray-values to the background, and this value is more sensitive than the gray-level variations. The text level stroke features are extracted using a multi-resolution wavelet transforms on the local image areas and the feature vectors are input to a SVM(Support Vector Machine) classifier for the verification. We have tested the proposed method using various kinds of the natural images and have confirmed that the extraction rates are very high even in complex background images.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.923-935
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• 2022

This paper deals with detection and classification of leaf diseases for phenomics systems. As the smart farm systems of plants are increased, It is important to determine quickly the abnormal growth of plants without supervisors. This paper considers the color distribution and shape information of leaf diseases, and designs two deep leaning networks in training the leaf diseases. In the first step, color distribution of input image is analyzed for possible diseases. In the second step, the image is first partitioned into small segments using mean shift clustering, and the color information of each segment is inspected by the proposed Color Network. When a segment is determined as disease, the shape parameters of the segment are extracted and inspected by proposed Shape Network to classify the leaf disease types in the third step. According to the experiments with two types of diseases (frogeye/rust and tipburn) for apple leaves and iceberg, the leaf diseases are detected with 92.3% recall for a segment and with 99.3% recall for an input image where there are usually more than two disease segments. The proposed method is useful for detecting leaf diseases quickly in the smart farm environment, and is extendible to various types of new plants and leaf diseases without additional learning.