• 제목/요약/키워드: image information theory

검색결과 388건 처리시간 0.029초

The Pattern Recognition System Using the Fractal Dimension of Chaos Theory

  • Shon, Young-Woo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제15권2호
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    • pp.121-125
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    • 2015
  • In this paper, we propose a method that extracts features from character patterns using the fractal dimension of chaos theory. The input character pattern image is converted into time-series data. Then, using the modified Henon system suggested in this paper, it determines the last features of the character pattern image after calculating the box-counting dimension, natural measure, information bit, and information (fractal) dimension. Finally, character pattern recognition is performed by statistically finding each information bit that shows the minimum difference compared with a normalized character pattern database.

Design of Unsharp Mask Filter based on Retinex Theory for Image Enhancement

  • Kim, Ju-young;Kim, Jin-heon
    • Journal of Multimedia Information System
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    • 제4권2호
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    • pp.65-73
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    • 2017
  • This paper proposes a method to improve the image quality by designing Unsharp Mask Filter (UMF) based on Retinex theory which controls the frequency pass characteristics adaptively. Conventional unsharp masking technique uses blurring image to emphasize sharpness of image. Unsharp Masking(UM) adjusts the original image and sigma to obtain a high frequency component to be emphasized by the difference between the blurred image and the high frequency component to the original image, thereby improving the contrast ratio of the image. In this paper, we design a Unsharp Mask Filter(UMF) that can process the contrast ratio improvement method of Unsharp Masking(UM) technique with one filtering. We adaptively process the contrast ratio improvement using Unsharp Mask Filter(UMF). We propose a method based on Retinex theory for adaptive processing. For adaptive filtering, we control the weights of Unsharp Mask Filter(UMF) based on the human visual system and output more effective results.

영상처리 이론 및 실습교육을 위한 통합교육시스템에 관한 연구 (The CAI systems for the image processing theory and practice)

  • 손병락;채옥삼
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 하계종합학술대회논문집
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    • pp.741-744
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    • 1998
  • In the area of the multimedia computer, the demand for the image processing engineer is large. However, there are not many engineers capable of developing practical systems. To teach practical image processing techniques, we need an intergrated education systems which can efficiently present the image processing theory and, at the same time, provide interactive experiments for the theory presented. In this paper, we propose an integrated education systems for the image processing. It consists of the theory presentation systems and the experiment systems. The theory presentation systems uspports multimedia display functions and HTML. It is tightly integrated with the experiment systems which developed based on the integrated image processing algorithm development system called Hello-vision.

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이산 모스 이론을 이용한 영역 분할 - 맘모그래피에의 응용 (Region Segmentation using Discrete Morse Theory - Application to the Mammography)

  • 한희일
    • 한국멀티미디어학회논문지
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    • 제22권1호
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    • pp.18-26
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    • 2019
  • In this paper we propose how to detect circular objects in the gray scale image and segment them using the discrete Morse theory, which makes it possible to analyze the topology of a digital image, when it is transformed into the data structure of some combinatorial complex. It is possible to get meaningful information about how many connected components and topologically circular shapes are in the image by computing the persistent homology of the filtration using the Morse complex. We obtain a Morse complex by modeling an image as a cubical cellular complex. Each cell in the Morse complex is the critical point at which the topological structure changes in the filtration consisting of the level sets of the image. In this paper, we implement the proposed algorithm of segmenting the circularly shaped objects with a long persistence of homology as well as computing persistent homology along the filtration of the input image and displaying in the form of a persistence diagram.

신경회로망 ICA를 이용한 혼합영상신호의 분리 (Blind Image Separation with Neural Learning Based on Information Theory and Higher-order Statistics)

  • 조현철;이권순
    • 전기학회논문지
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    • 제57권8호
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    • pp.1454-1463
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    • 2008
  • Blind source separation by independent component analysis (ICA) has applied in signal processing, telecommunication, and image processing to recover unknown original source signals from mutually independent observation signals. Neural networks are learned to estimate the original signals by unsupervised learning algorithm. Because the outputs of the neural networks which yield original source signals are mutually independent, then mutual information is zero. This is equivalent to minimizing the Kullback-Leibler convergence between probability density function and the corresponding factorial distribution of the output in neural networks. In this paper, we present a learning algorithm using information theory and higher order statistics to solve problem of blind source separation. For computer simulation two deterministic signals and a Gaussian noise are used as original source signals. We also test the proposed algorithm by applying it to several discrete images.

Review of the Application of Wavelet Theory to Image Processing

  • Vyas, Aparna;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • 제5권6호
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    • pp.403-417
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    • 2016
  • This paper reviews recent published works dealing with the application of wavelets to image processing based on multiresolution analysis. After revisiting the basics of wavelet transform theory, various applications of wavelets and multiresolution analysis are reviewed, including image denoising, image enhancement, super-resolution, and image compression. In addition, we introduce the concept and theory of quaternion wavelets for the future advancement of wavelet transform and quaternion multiresolution applications.

Scale-Space 이론에 기초한 내용 기반 영상 검색 (Content-Based Image Retrieval using Scale-Space Theory)

  • 오정범;문영식
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제26권1호
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    • pp.150-150
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    • 1999
  • In this paper, a content-based image retrieval scheme based on scale-space theory is proposed. The existing methods using scale-space theory consider all scales for image retrieval,thereby requiring a lot of computation. To overcome this problem, the proposed algorithm utilizes amodified histogram intersection method to select candidate images from database. The relative scalebetween a query image and a candidate image is calculated by the ratio of histograms. Feature pointsare extracted from the candidates using a corner detection algorithm. The feature vector for eachfeature point is composed of RGB color components and differential invariants. For computing thesimilarity between a query image and a candidate image, the euclidean distance measure is used. Theproposed image retrieval method has been applied to various images and the performance improvementover the existing methods has been verified.

항공사진과 지형공간정보체계를 이용한 수치영상지도 제작연구 (Production of Digital Image Map using Aerial Photo and Geospatial Information System)

  • 손덕재
    • 대한공간정보학회지
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    • 제5권2호
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    • pp.207-220
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    • 1997
  • 본 연구에서는 항공사진과 지형공간정보체계를 이용하여 수치영상지도를 제작하기 위한 효율적 방안을 고찰하고, 저가의 개인용 컴퓨터시스템을 기본으로 하는 지형공간정보체계를 이용하여 수치항공사진 영상과 수치지형도를 중첩함으로써, 지형판독성과 활용성이 높은 수치영상지도를 제작하는 실험적 방안을 연구한다. 이를 위하여 지상좌표의 결정, 수치영상처리, 수치표고모형의 생성에 대하여 고찰한 다음, 수치영상지도제작에 필요한 영상자료 입출력, 수치편위미분수정, 항공사진을 이용한 정사투영상의 생성에 관련된 방법을 고찰하고, 수치영상지도를 실험제작하여 그 활용방안을 제시하였다.

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The Improvement of Rough- set Theory Histogram in Color- image Segmentation

  • Zheng, Qi;Lee, Hyo Jong
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2011년도 추계학술발표대회
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    • pp.429-430
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    • 2011
  • Roughness set theory is a popular topic to use in color-image segmentation. A new popular color image segmentation algorithm is proposed by scientists with the point using traditional histogram and Histon construct roughness set histogram. But, there is still a problem about that is the correlativity of color vector in roughness set histogram, which take an inactive effect in the process of color-image segmentation. Therefore, this paper represents further research based on this and proposed an improved method proved through lot of experiments. The experimental result reduces the correlativity of color vector in roughness set histogram and calculation time remarkably.