• Title/Summary/Keyword: 이미지 향상

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Design and Construction of Image Dataset for Finger Direction Detection (손가락 방향 감지를 위한 이미지 데이터셋 설계 및 구축)

  • Kang, Gi Deok;Lee, Dong Myung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.31-33
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    • 2021
  • In this paper, a dataset was designed and built to improve the accuracy of finger direction detection using an object detection algorithm based on You Only Look Once (YOLO). In order to improve the object detection performance, about 200 finger image data sets were trained, and to confirm that the detection accuracy differs from each other according to the angle of the palm, 50 comparison groups of different angles were configured and tested. As a result of the experiment, it was confirmed that the detection accuracy of palm located in a direction close to 90° is higher than that of other angles.

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Vehicle License Plate Recognition System Using the Cautious Classifier and the Weighted Instance Method (신중한 분류기와 학습 예제 가중치 조정을 이용한 차량번호판인식시스템의 인식성능 향상 방안)

  • Baik, Nam Cheol;Lee, Sang Hyup;Ryu, Kwang Ryul
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.4D
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    • pp.549-551
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    • 2006
  • Vehicle License Plate Recognition System reads information from vehicles license plate using image detection devices. Of many applications provided by Vehicle License Plate Recognition System, some, such as speed enforcing system, can be problematic when the system incorrectly scans letters or numbers from a vehicle's license plate. Using Cautious Classifier avoids such problems by discarding the scanned information when the confidence level is doubted to be low. This study develops the License Plate Recognition System using Cautious Classifier and investigates effectiveness of applying the Weighted Instance Method to improve the performance of Cautious Classifier.

Genetic Algorithm Based Feature Reduction For Depth Estimation Of Image (이미지의 깊이 추정을 위한 유전 알고리즘 기반의 특징 축소)

  • Shin, Sung-Sik;Gwun, Ou-Bong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.2
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    • pp.47-54
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    • 2011
  • This paper describes the method to reduce the time-cost for depth estimation of an image by learning, on the basis of the Genetic Algorithm, the image's features. The depth information is estimated from the relationship among features such as the energy value of an image and the gradient of the texture etc. The estimation-time increases due to the large dimension of an image's features used in the estimating process. And the use of the features without consideration of their importance can have an adverse effect on the performance. So, it is necessary to reduce the dimension of an image's features based on the significance of each feature. Evaluation of the method proposed in this paper using benchmark data provided by Stanford University found that the time-cost for feature extraction and depth estimation improved by 60% and the accuracy was increased by 0.4% on average and up to 2.5%.

A Study on Feature Information Parsing of Video Image Using Improved Moment Invariant (향상된 불변모멘트를 이용한 동영상 이미지의 특징정보 분석에 관한 연구)

  • Lee, Chang-Soo;Jun, Moon-Seog
    • Journal of Korea Multimedia Society
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    • v.8 no.4
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    • pp.450-460
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    • 2005
  • Today, multimedia information is used on the internet and various social areas by rapid development of computer and communication technology. Therefor, the usage is growing dramatically. Multimedia information analysis system is basically based on text. So, there are many difficult problems like expressing ambiguity of multimedia information, excessive burden of works in appending notes and a lack of objectivity. In this study, we suggest a method which uses color and shape information of multimedia image partitions efficiently analyze a large amount of multimedia information. Partitions use field growth and union method. To extract color information, we use distinctive information which matches with a representative color from converting process from RGB(Red Green Blue) to HSI(Hue Saturation Intensity). Also, we use IMI(Improved Moment Invariants) which target to only outline pixels of an object and execute computing as shape information.

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Editorial Design Element Analysis in Annual Report for Corporate PR (기업 홍보물 애뉴얼리포트의 편집디자인 요소 분석)

  • Kim, Sung-Hak
    • The Journal of the Korea Contents Association
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    • v.14 no.1
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    • pp.119-127
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    • 2014
  • As keen marketing competition for increasing corporate image has been begun, the creative level of annual report design, which is deeply involved with investment, has became a fundamental measure of corporate value. Good commercial design has to have both practical and aesthetic aspect. For make more creative annual report project. it's worth to find world design trend in practical way. The point of study focuses and sorts on physical properties of out-put works by the view point of editorial design, and tries to find the possibility of common design style. It analyzes key message, pagination plan and feature pages of 2013 ARC awarded annual report works in interior design category. The visual image and typographic style study of awarded works will help planner and designer who develop annual report project, because this research data reduces their process. Then it's possible to have more opportunities to create project and supports background material for making a presentation for clients.

A Study on the Detection of Fallen Workers in Shipyard Using Deep Learning (딥러닝을 이용한 조선소에서 쓰러진 작업자의 검출에 관한 연구)

  • Park, Kyung-Min;Kim, Seon-Deok;Bae, Cherl-O
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.26 no.6
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    • pp.601-605
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    • 2020
  • In large ships with complex structures, it is difficult to locate workers. In particular, it is not easy to detect when a worker falls down, making it difficult to respond quickly. Thus, research is being conducted to detect fallen workers using a camera or by attaching a device to the body. Existing image-based fall detection systems have been designed to detect a person's body parts; hence, it is difficult to detect them in various ships and postures. In this study, the entire fall area was extracted and deep learning was used to detect the fallen shipworker based on the image. The data necessary for learning were obtained by recording falling states at the shipyard. The amount of learning data was augmented by flipping, resizing, and rotating the image. Performance evaluation was conducted with precision, reproducibility, accuracy, and a low error rate. The larger the amount of data, the better the precision. In the future, reinforcing various data is expected to improve the effectiveness of camera-based fall detection models, and thus improve safety.

Correlation Research between Objective and Subjective Image Quality Assessment (객관적 화질 평가와 주관적 화질 평가의 상관관계 연구)

  • Park, Hyung-Ju;Har, Dong-Hwan
    • The Journal of the Korea Contents Association
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    • v.11 no.8
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    • pp.68-76
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    • 2011
  • Due to the high interests of image quality by consumers, the concerned market becomes more heated. Recent digital camera development tendency shows to perform the higher image quality to meet consumers demand of quality satisfaction. However it is hard to confirm that development of objective image quality performance means positive subjective image quality preference. And also, we cannot find out the previous researches concerned on correlation between objective and subjective image quality comparison. Therefore, it is necessary to analyze the consumers preferred images based on objective image quality performance. Throughout this paper, we analyze statistical correlation between the objective and subjective image quality assessment methods by using ISO standards. In these results, we try to find attributes that enhance image quality. We suggest not only to analyze and reflect on customers' preferences, but also to pursue the high quality image performance practically. We expect the results of this paper to positively influence product development.

X-ray Image Correction Model for Enhanced Foreign Body Detection in Metals (금속 내부의 이물질 검출 향상을 위한 X-ray 영상 보정 모델)

  • Kim, Won
    • Journal of the Korea Convergence Society
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    • v.10 no.10
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    • pp.15-21
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    • 2019
  • X-rays with shorter wavelengths than ultraviolet light have very good penetration power. It is convergence in industrial and medical fields has been used a lot. n particular, in the industrial field, various researches have been conducted on the detection of foregin body inside metal that can occur in the production process of products such as metal using x-ray, a non-destructive inspection device. Detectors are becoming increasingly popular for the popularization of DR (Digital Radiography) photography methods that digitally acquire X-ray video images. However, there are cases where foreign body detection is impossible depending on the sensor noise and sensitivity inside the detector. When producing a metal product, since the defective rate of the produced product may increase due to contamination of the foreign body, accurate detection is necessary. In this paper, we provide a correction model for X-ray images acquired in order to improve the efficiency of defect detection such as foreign body inside metal. When applied to defect detection in the production process of metal products through the proposed model, it is expected that the detection of product defects can be processed accurately and quickly.

An Index-Building Method for Boundary Matching that Supports Arbitrary Partial Denoising (임의의 부분 노이즈제거를 지원하는 윤곽선 매칭의 색인 구축 방법)

  • Kim, Bum-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.11
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    • pp.1343-1350
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    • 2019
  • Converting boundary images to time-series makes it feasible to perform boundary matching even on a very large image database, which is very important for interactive and fast matching. In recent research, there has been an attempt to perform fast matching considering partial denoising by converting the boundary image into time series. In this paper, to improve performance, we propose an index-building method considering all possible arbitrary denoising parameters for removing arbitrary partial noises. This is a challenging problem since the partial denoising boundary matching must be considered for all possible denoising parameters. We propose an efficient single index-building algorithm by constructing a minimum bounding rectangle(MBR) according to all possible denoising parameters. The results of extensive experiments conducted show that our index-based matching method improves the search performance up to 46.6 ~ 4023.6 times.

Improved Transformer Model for Multimodal Fashion Recommendation Conversation System (멀티모달 패션 추천 대화 시스템을 위한 개선된 트랜스포머 모델)

  • Park, Yeong Joon;Jo, Byeong Cheol;Lee, Kyoung Uk;Kim, Kyung Sun
    • The Journal of the Korea Contents Association
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    • v.22 no.1
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    • pp.138-147
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    • 2022
  • Recently, chatbots have been applied in various fields and have shown good results, and many attempts to use chatbots in shopping mall product recommendation services are being conducted on e-commerce platforms. In this paper, for a conversation system that recommends a fashion that a user wants based on conversation between the user and the system and fashion image information, a transformer model that is currently performing well in various AI fields such as natural language processing, voice recognition, and image recognition. We propose a multimodal-based improved transformer model that is improved to increase the accuracy of recommendation by using dialogue (text) and fashion (image) information together for data preprocessing and data representation. We also propose a method to improve accuracy through data improvement by analyzing the data. The proposed system has a recommendation accuracy score of 0.6563 WKT (Weighted Kendall's tau), which significantly improved the existing system's 0.3372 WKT by 0.3191 WKT or more.