• 제목/요약/키워드: Image comparison

검색결과 2,403건 처리시간 0.033초

화면확대를 위한 보간 방식의 새로운 성능 평가 방법 (A New Performance Assesment Methods for Interpolated Image Enlargement)

  • 은진화;조화현;권병헌;최명렬
    • 대한전자공학회:학술대회논문집
    • /
    • 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
    • /
    • pp.58-61
    • /
    • 2000
  • In this paper, we propose a new performance comparison method of various Interpolation methods for image enlargement The conventional methods employs PSNR and edge characteristic evaluation for performance comparison of interpolation methods. The proposed performance comparison method uses the position Information for each difference pixel's value and the frequency characteristic information between original image and Interpolated image. The proposed methods might be useful for performance comparison of various Interpolation methods through the computer simulation.

  • PDF

위성영상을 이용한 토지이용 변화 검색기법 비교연구 (Comparison of Land Use Change Detection Methods with Satellite Image)

  • 박순호;김우관
    • 한국지역지리학회지
    • /
    • 제5권1호
    • /
    • pp.137-150
    • /
    • 1999
  • 우리나라에서 위성자료를 이용한 토지이용에 관한 연구는 현황분석이 중심이고, 토지이용 변화에 관한 연구는 분석기법에 대한 적실성 평가 없이 특정기법이 적용되어 왔다. 본 연구는 도시지역의 토지이용 변화 검색에 많이 활용되고 있는 다섯 가지 토지이용 변화 검색기법을 선정하여 대구광역시 북구를 사례로 각 검색기법의 정확도를 비교 분석하였다. 핵심데이터는 1994년과 1997년에 촬영한 Landsat TM영상과 항공사진이다. 위성자료를 이용한 토지이용 변화검색에는 pre-classification comparison method가 post-classification comparison method보다 효과적이었다. Pre-classification comparison methods 중에서는 image differencing method가, 특히 임계치 1.0에서의 image differencing method의 DIF2 변화이미지의 경우가 가장 정확도가 높게 나타났다.

  • PDF

SNS 여성 이용자의 신체불만족과 식이장애에 미치는 영향요인에 관한 연구: 대상화이론과 사회비교이론을 중심으로 (A Study on the Factors Influencing the Body Dissatisfaction and Eating Disorders of Female Social Network Service Users: Focusing on Objectification theory and Social Comparison theory)

  • 김다희;박민정
    • 한국의류산업학회지
    • /
    • 제22권4호
    • /
    • pp.469-480
    • /
    • 2020
  • The study investigated the effects of SNS usage on 20s and 30s female SNS users' internalization of thin body, body surveillance, appearance upper comparison, body dissatisfaction and eating disorders based on objectification theory and social comparison theory. The study examined differences on SNS usage and body image variables between high and low groups of SNS envy and self-compassion. Social Network Service (SNS) is used as a contemporary marketing tool for brands and companies. It also influences the body image of female SNS users. The survey used an online survey company for female SNS users in their 20s and 30s to analyze the effect of SNS usage. The results showed that SNS usage significantly impacted the internalization of a thin body, body surveillance and appearance upper comparison. The internalization of thin body also had a significant impact on body surveillance and appearance upper comparison. Appearance upper comparison positively affected body dissatisfaction and eating disorders. Finally, the group with higher SNS envy showed higher SNS usage, internalization of thin body, body surveillance, appearance upper comparison, body dissatisfaction and eating disorders. The group with higher self-compassion showed opposite results. This study provided a theoretical expansion for a SNS and female body image study with objectification theory and social comparison theory. It also suggests positive SNS marketing strategies use for brands. Lastly, this study emphasized the importance of the proper use of SNS to protect the body image of SNS users.

Performance Comparison According to Image Generation Method in NIDS (Network Intrusion Detection System) using CNN

  • Sang Hyun, Kim
    • International journal of advanced smart convergence
    • /
    • 제12권2호
    • /
    • pp.67-75
    • /
    • 2023
  • Recently, many studies have been conducted on ways to utilize AI technology in NIDS (Network Intrusion Detection System). In particular, CNN-based NIDS generally shows excellent performance. CNN is basically a method of using correlation between pixels existing in an image. Therefore, the method of generating an image is very important in CNN. In this paper, the performance comparison of CNN-based NIDS according to the image generation method was performed. The image generation methods used in the experiment are a direct conversion method and a one-hot encoding based method. As a result of the experiment, the performance of NIDS was different depending on the image generation method. In particular, it was confirmed that the method combining the direct conversion method and the one-hot encoding based method proposed in this paper showed the best performance.

Midjourney와 Stable Diffusion을 이용한 AI 생성 이미지의 차이 비교 (Comparison of the Differences in AI-Generated Images Using Midjourney and Stable Diffusion)

  • 부이두엉화이린;이강희
    • 한국컴퓨터정보학회:학술대회논문집
    • /
    • 한국컴퓨터정보학회 2023년도 제68차 하계학술대회논문집 31권2호
    • /
    • pp.563-564
    • /
    • 2023
  • Midjourney and Stable Diffusion are two popular AI-generated image programs nowadays. With AI's outstanding image-generation capabilities, everyone can create artistic paintings in just a few minutes. Therefore, "Comparison of differences between AI-generated images using Midjourney and Stable Diffusion" will help see each program's advantages and assist the users in identifying the tool suitable for their needs.

  • PDF

시맨틱 웹 기반의 이미지 정색을 이용한 비교 쇼핑 시스템 (Comparison Shopping Systems using Image Retrieval based on Semantic Web)

  • 이기성;유영훈;조근식;김흥남
    • 지능정보연구
    • /
    • 제11권2호
    • /
    • pp.1-15
    • /
    • 2005
  • 쇼핑몰들의 상품 정보를 효과적으로 비교할 수 있는 비교 쇼핑(comparison shopping) 시스템에서 사용자가 찾고자하는 상품에 대한 정확한 지식이 없이 검색할 경우, 불필요한 검색 결과로 인해 시스템의 효용성을 떨어지고, 사용자는 많은 시간을 소비하게 된다. 이러한 문제를 해결하기 위해서 시맨틱 웹 기반의 이미지 검색을 이용한 비교 쇼핑 시스템(Comparison Shopping Systems using Image Retrieval based on Semantic Web)을 제안한다. 제안된 시스템에서는 각 쇼핑몰들의 상품 이미지들을 온톨로지(Ontology) 기반으로 주석(annotation)처리한 후, 주석처리 된 이미지들을 통해 쇼핑몰을 구축하게 된다. 사용자는 이렇게 생성된 쇼핑몰에서 복잡한 키워드 검색을 이미지 검색으로 대체하여, 자신의 요구사항을 반영하고, 보다 정확한 검색을 할 수 있게 된다. 제안된 시스템의 성능평가를 위해 기존의 키워드 검색 기반 시스템과 단순 시맨틱 웹 기반의 비교 쇼핑 시스템의 성능을 비교 평가하였다. 그 결과, 시맨틱 웹 기반의 이미지 검색을 이용한 비교쇼핑 시스템이 키워드 검색기반과 시맨틱 웹 기반의 비교 쇼핑 시스템보다 평균적으로 50%, 20% 향상된 성능을 보였다.

  • PDF

Digital Change Detection by Post-classification Comparison of Multitemporal Remotely-Sensed Data

  • Cho, Seong-Hoon
    • 대한원격탐사학회지
    • /
    • 제16권4호
    • /
    • pp.367-373
    • /
    • 2000
  • Natural and artificial land features are very dynamic, changing somewhat repidly in our lifetime. It is important that such changes are inventoried accurately so that the physical and human processes at work can be more fully understood. Change detection is a technique used to determine the change between two or more time periods of a particular object of study. Change detection is an important process in monitoring and managing natural resources and urban development because it provides quantitative analysis of the spatial distribution in the population of interest. The purpose of this research is to detect environmental changes surrounding an area of Mountain Moscow, Idaho using Landsat Thematic Maper (TM) images of (July 8, 1990 and July 20, 1991). For accurate classification, the Image enhancement process was performed for improving the image quality of each image. A SPOT image (Aug. 14, 1992) was used for image merging in this research. Supervised classification was performed using the maximum likelihood method. Accuracy assessments were done for each classification. Two images were compared on a pixel-by-pixel basis using the post-classification comparison method that is used for detecting the changes of the study area in this research. The 'from-to' change class information can be detected by post classification comparison using this method and we could find which class change to another.

Comparison of Feature Selection Processes for Image Retrieval Applications

  • Choi, Young-Mee;Choo, Moon-Won
    • 한국멀티미디어학회논문지
    • /
    • 제14권12호
    • /
    • pp.1544-1548
    • /
    • 2011
  • A process of choosing a subset of original features, so called feature selection, is considered as a crucial preprocessing step to image processing applications. There are already large pools of techniques developed for machine learning and data mining fields. In this paper, basically two methods, non-feature selection and feature selection, are investigated to compare their predictive effectiveness of classification. Color co-occurrence feature is used for defining image features. Standard Sequential Forward Selection algorithm are used for feature selection to identify relevant features and redundancy among relevant features. Four color spaces, RGB, YCbCr, HSV, and Gaussian space are considered for computing color co-occurrence features. Gray-level image feature is also considered for the performance comparison reasons. The experimental results are presented.