• Title/Summary/Keyword: Color classification

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A study on morphological and pattern analysis in two kinds of Aconiti Radix (부자(附子)와 초오(草烏)의 내외부형태(內外部形態)와 패턴분석연구)

  • Kang, Gyun-Heok;Choi, Go-Ya;Kim, Hong-Jun;Ju, Young-Sung
    • Korean Journal of Oriental Medicine
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    • v.12 no.1
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    • pp.23-38
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    • 2006
  • The taxonomic list of specific features in external and internal shape and the pattern analysis of Aconitum carmichalei $D_{EBX}$ as the original plant of Aconiti Lateralis Radix Preparata and Aconitum cliiare Dc as the original plant of Aconiti Ciliare Tuber are as follows. 1. Aconitum carmichalei $D_{EBX}$ has tri-palmately parted leaves, petiole in lower leaves, and its ovary has short hair. Whereas Aconitum cliare Dc has $3{\sim}4$ parted leaves, long petiole, and its ovary has not hair. 2. Aconitum carmichalei $D_{EBX}$ has cylinder shape is relatively small in length and diameter, is greyish brown blacky brown in outer surface, greyish $white{\sim}dark$ gray in section. 3. According to the collection place, there is a remarkable difference in the physical shape of herbal states. Aconiti Lateralis Radix Preparate(medicated in Korea) is more transparent blacky brown color than Aconiti Lateralis Fadix Preparata(medicated in Chian). Also Black Aconi Radix(墨附片) has exodermis and White Aconi Radix(白附片) has not. 4. The internal characteristics entirely correspond to in internal shape described in the literatures, Only it is possible to discriminate between black Aconi Radix(墨附片) and White Aconi Radix(白附片) by the existence of cork layer. The classification between Aconiti Lateralis Radix Preparata and Aconiti Ciliare Tuber makes entirely Tuber makes entirely remarkable difference in the physical shape of cambium layer Namely, in shape of cambium layer the kinds of Aconiti lateralis Radix Prepala has horn-like shape and the kinds of Aconiti Ciliare Tuber has circle-like shape. 5. In the peak of examination substance in comparison to Rt of the index material diterpene alkaloid mesaconitine, aconitine, hypaconitine chromatogram Aconiti Ciliare Tuber is higher than in Aconiti Lateralis Radix Preparata This explain that the component changes after the process of medicine. 6. In the Content of mesaconitine, aconitine and hypaconitime Aconiti Ciliare Tuber is higher than Aconiti Lateralis Radix Preparata. 7. In Aconiti Lateralis Radix Preparata, aconitine, hypaconitine and mesaconitine each appears in Rf 0.46, 0.54, 0.32. But except Aconiti Ciliare Tuber the band does not appear. For the future, such results will be used as the basic source of additional research, and a far-reaching comparative study is needed to distinguish between many kinds of same genus-degree of relatedness.

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Illumination Mismatch Compensation Algorithm based on Layered Histogram Matching by Using Depth Information (깊이 정보에 따른 레이어별 히스토그램 매칭을 이용한 조명 불일치 보상 기법)

  • Lee, Dong-Seok;Yoo, Ji-Sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.8C
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    • pp.651-660
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    • 2010
  • In this paper, we implement an efficient histogram-based prefiltering to compensate the illumination mismatches in regions between neighboring views. In multi-view video, such illumination disharmony can primarily occur on account of different camera location and orientation and an imperfect camera calibration. This discrepancy can cause the performance decrease of multi-view video coding(MVC) algorithm. A histogram matching algorithm can be exploited to make up for these differences in a prefiltering step. Once all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching, the coding efficiency of MVC is improved. However general frames of multi-view video sequence are composed of several regions with different color composition and their histogram distribution which are mutually independent of each other. In addition, the location and depth of these objects from sequeuces captured from different cameras can be different with different frames. Thus we propose a new algorithm which classify a image into several subpartitions by its depth information first and then histogram matching is performed for each region individually. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with the conventional image-based algorithms.

Image Quality for TV Genre Depending on Viewers Experience (시청자 경험에 의한 TV장르별 화질)

  • Park, YungKyung
    • Journal of Broadcast Engineering
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    • v.26 no.3
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    • pp.308-320
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    • 2021
  • Conventional image quality studies have been focused on 'naturalness' and has relied on memory color. Memory colors are mainly formed for familiar objects with prior experience, and the more faithfully these memories are reflected, the more naturalness of the reproduced image quality increases. In particular, the brightness and saturation of memory colors play an important role in increasing the preference of image quality as well as naturalness. Therefore, in the case of existing image quality studies, image quality characteristics were studied focusing on natural objects and people with memory. We extracted representative images of each genre (sports, documentaries, news, entertainment and music, and movies), adjusted the brightness, contrast, and saturation of each image, and conducted an experiment to evaluate perceived quality. Based on situational context, the results of this classification indicated that genres of television content can be divided into two categories: proximate and indirect experiences. Proximate experience best characterizes outdoor sports, dramas, and nature documentaries, where their image qualities have shown to have a strong correlation with brightness and contrast. On the other hand, indirect experience best characterizes news, music shows and SF/action movies. The image quality perception for indirect experiences was shown to be closely related to and optimized by contrast and saturation.

Automatic Construction of Deep Learning Training Data for High-Definition Road Maps Using Mobile Mapping System (정밀도로지도 제작을 위한 모바일매핑시스템 기반 딥러닝 학습데이터의 자동 구축)

  • Choi, In Ha;Kim, Eui Myoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.3
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    • pp.133-139
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    • 2021
  • Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.

Human Skeleton Keypoints based Fall Detection using GRU (PoseNet과 GRU를 이용한 Skeleton Keypoints 기반 낙상 감지)

  • Kang, Yoon Kyu;Kang, Hee Yong;Weon, Dal Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.127-133
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    • 2021
  • A recent study of people physically falling focused on analyzing the motions of the falls using a recurrent neural network (RNN) and a deep learning approach to get good results from detecting 2D human poses from a single color image. In this paper, we investigate a detection method for estimating the position of the head and shoulder keypoints and the acceleration of positional change using the skeletal keypoints information extracted using PoseNet from an image obtained with a low-cost 2D RGB camera, increasing the accuracy of judgments about the falls. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion-analysis method. A public data set was used to extract human skeletal features, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than a conventional, primitive skeletal data-use method.

Detection of Wildfire Smoke Plumes Using GEMS Images and Machine Learning (GEMS 영상과 기계학습을 이용한 산불 연기 탐지)

  • Jeong, Yemin;Kim, Seoyeon;Kim, Seung-Yeon;Yu, Jeong-Ah;Lee, Dong-Won;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.38 no.5_3
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    • pp.967-977
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    • 2022
  • The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO2), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

Classification of Diabetic Retinopathy using Mask R-CNN and Random Forest Method

  • Jung, Younghoon;Kim, Daewon
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.12
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    • pp.29-40
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    • 2022
  • In this paper, we studied a system that detects and analyzes the pathological features of diabetic retinopathy using Mask R-CNN and a Random Forest classifier. Those are one of the deep learning techniques and automatically diagnoses diabetic retinopathy. Diabetic retinopathy can be diagnosed through fundus images taken with special equipment. Brightness, color tone, and contrast may vary depending on the device. Research and development of an automatic diagnosis system using artificial intelligence to help ophthalmologists make medical judgments possible. This system detects pathological features such as microvascular perfusion and retinal hemorrhage using the Mask R-CNN technique. It also diagnoses normal and abnormal conditions of the eye by using a Random Forest classifier after pre-processing. In order to improve the detection performance of the Mask R-CNN algorithm, image augmentation was performed and learning procedure was conducted. Dice similarity coefficients and mean accuracy were used as evaluation indicators to measure detection accuracy. The Faster R-CNN method was used as a control group, and the detection performance of the Mask R-CNN method through this study showed an average of 90% accuracy through Dice coefficients. In the case of mean accuracy it showed 91% accuracy. When diabetic retinopathy was diagnosed by learning a Random Forest classifier based on the detected pathological symptoms, the accuracy was 99%.

Escape Route Prediction and Tracking System using Artificial Intelligence (인공지능을 활용한 도주경로 예측 및 추적 시스템)

  • Yang, Bum-suk;Park, Dea-woo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.225-227
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    • 2022
  • Now In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office in Seoul has built a control center for CCTV control and is building information such as people, vehicle types, license plate recognition and color classification into big data through 24-hour artificial intelligence intelligent image analysis. Seoul Metropolitan Government has signed MOUs with the Ministry of Land, Infrastructure and Transport, the National Police Agency, the Fire Service, the Ministry of Justice, and the military base to enable rapid response to emergency/emergency situations. In other words, we are building a smart city that is safe and can prevent disasters by providing CCTV images of each ward office. In this paper, the CCTV image is designed to extract the characteristics of the vehicle and personnel when an incident occurs through artificial intelligence, and based on this, predict the escape route and enable continuous tracking. It is designed so that the AI automatically selects and displays the CCTV image of the route. It is designed to expand the smart city integration platform by providing image information and extracted information to the adjacent ward office when the escape route of a person or vehicle related to an incident is expected to an area other than the relevant jurisdiction. This paper will contribute as basic data to the development of smart city integrated platform research.

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Nondestructive Quantification of Corrosion in Cu Interconnects Using Smith Charts (스미스 차트를 이용한 구리 인터커텍트의 비파괴적 부식도 평가)

  • Minkyu Kang;Namgyeong Kim;Hyunwoo Nam;Tae Yeob Kang
    • Journal of the Microelectronics and Packaging Society
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    • v.31 no.2
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    • pp.28-35
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    • 2024
  • Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

현대여성(現代女性)의 의복의식(衣服意識)에 관한 조사(調査) 연구(硏究) - 서울 지역(地域)의 양복(洋服) 착용자(着用者)를 중심(中心)으로 -

  • Lee, Hee-Myung
    • Journal of the Korean Society of Costume
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    • v.2
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    • pp.73-88
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    • 1978
  • This article is an attempt to explain, at least in part, the contemporary Korean women's consciousness of Western Dreasses. As time changes, the role of clothing undergoes varisous transitions, while values and ways of life are constantly in change. It is, therefore, proper and appropriate to recognize as among the major aspects of social psychology such phenomenon as interests, understanding of clothing, the choice of a dress, and attitudes toward clothing, etc. The purpose of this study is to discover problems concerning and their clothing and their solutions, by means of a surveying approach. The method of research used is based upon questionares distributed to parents of first-year pupils in elementary schools and to female clerks working in offices, covering the period from August through October, 1976. The number of the questionares distrubuted totalled 600, and 526 were returned to the research to be utilized for analysis. The contents of the survey included such things as values concerning clothing, kinds of clothing and their practical use, the selection of clothing and the method of purchase, fashions, etc. The classification of aquisition are self-made clothing, clothing made to order and ready-made materials. It is composed of 25 items, including affirmative reasons as well as negative ones. The processing of the material returned was made by using the computer, and based upon classifications such as ages, monthly income, occupations; thus diagraming the result in percentages. The conclusion made and the improvements proposed are as follows: 1. The values of clothing were placed on the expression of the wearer's personality (32.7) and on eauty(28. 6%). The lower age group places is stress upon the expression of personality, while the higher age group stresses beauty. About 50% of wearers are contented with their clothing, their clothing, the rest of whom them indicating their dissatisfaction with what they wear. As to designs at the time of selection, about 46% indicated their preference of personal expression, 31.8% on usefulness. In selecting material, practicality is emphasized; in selecting patterns, single color is preferred. In short, personal expression and esthetic values are primary, with consideration of practicality in mind. 2. The classification of clothing according to their uses indicates the highest numbers in normal wear (home wears) and clothings to be worn outside home. As to evening dresses, (party dress) only one or two articles were checked by many, and no such article was clamed to be possessed by most. The highest ratio of wearing was shown in the case of home wear (47.3%) and clothing to be worn outside the home, which is 55.8%. The budget for one article of clothing was greatest in the case of home wear, and clothing worn outside the home. Many used both kinds of articles for the same purpose. It is desirable, therefore, that the kinds of clothing should be varied according to the purpose for which they are worn, and that clothing appropriate for that purpose should be worn. 3. The motivation for purchasing clothing was highly chosen in the item of seasonal change, which was 55.7%; Clothing deliberately made was indicated by 45.2%. In the mothods of purchasing clothing, clothing made to order and ready-made was indicated by 44.4%, which is the highest; Clothing made to order was 25.4%, and self-sewing was 1.1%, which is the lowest. (1) In the case of self-sewing, "I like it but it is very hard," was checked by 43.6%; "It is so difficult that I cannot wear such clothing" was checked by 13.3%. From these, we can conclude that the questionees are willing to make clothing by themselves, but techniques involved in sewing and at her problems involved in the skill are complicated but when those problems are eliminated there is a possibility for practice. The response checked by questionees concerning the self-sewing was, "It's economical", which is a clear indication that many questionees are positive for self-sewing. It is generally believed that ready-made clothing is cheaper, but it is not necessarily so. In consideration of the quality of clothing, self-sewing is a necessity, and it is desirable that it should be encouraged. (3) Problems involved in ready-made clothing, such as designs, skills, size (fitting) should be eliminated. When these problems are scientifically gotten rid of, it is possible that affirmative returns will be expected. Affirmative responses such as "Ready-made clothing is economical," "You can select there on the spot," are good signs that many women expect to wear ready-made clothing. It is in this sense that the prospect for ready-made clothing is brighter when much development for ready-made clothing is on the way. 4. Much concern for fashion are checked in such item of questions as "Fashionable clothing in the show window," "Clothes worn by women." The first item was checked by 50.1 %, and the second was checked by 48.6%. The reason for following fashion is "Because many people wear them," which was indicated by 30.4%. The reason for not following fashion is "It is too expensive," which was checked by 29.6%. The 26.2% of the answers indicated that "Fashionable clothing is devoid of personality," The influences of fashion over the development of fashion over the development of clothing are two-fold: Esthetic and active. It is not to be deniable that people follow fashion more or less. 1978.9>

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