• Title/Summary/Keyword: 지역 히스토그램 비교

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Scene Change Detection Using Local $X^2$ (지역적 $X^2$를 이용한 장면전환검출 기법)

  • Shin, Seong-Yoon;Baik, Seong-Eun;Pyo, Seong-Bae;Rhee, Yang-Won
    • KSCI Review
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    • v.15 no.1
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    • pp.203-207
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    • 2007
  • 본 논문에서는 비디오의 분할을 위하여 먼저 기존에 제안되었던 차이 값 추출방법들의 단점들을 극복하고 장점을 최대한 활용할 수 있으며 급진적 장면전환부터 점진적 장면전환까지 모두 예측할 수 있는 강건하고 복합적인 차이 값 추출방법에 대해서 제안한다. 이 방법은 지역적 $X^2$-테스트로서 기존의 컬러 히스토그램과 $X^2$-테스트를 결합한 방법이다. 본 논문을 위하여 기존의 히스토그램 기반 알고리즘과 비교하여 좋은 성능을 보여주는 $X^2$-테스트를 변형하였고, 컬러 값의 세분화 작업에 따른 검출효과를 높이기 위하여 명암도 등급에 따른 가중치를 적용한 지역적 $X^2$-테스트를 이용하였다. 이 방법은 복잡하고 다양한 시세계의 영상 변화를 가장 일반적이고 표준화된 방법으로 분석하고 분할하며 표현할 수 있는 방법이다. 기존의 $X^2$-테스트와 제안된 지역적 $X^2$-테스트 방법의 비교는 실험을 통해 입증되었다.

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색상 보정을 이용한 안개 제거 알고리즘

  • Eom, Tae-Ha;Lee, Geun-Min;Kim, Won-Ha
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2012.07a
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    • pp.19-22
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    • 2012
  • 본 논문에서는 히스토그램 분석을 통한 안개 강도 측정과 제거, 그리고 HSI채널에서 색상을 보정하는 방법을 제안한다. 이를 위해 영상에서 안개가 많은 지역과 적은 지역을 히스토그램을 통해 분석하고 안개 강도 맵을 만들어 안개의 양에 따라 안개를 제거한다. 안개로 인하여 악화된 영상의 색상은 HSI 공간에서 분석하여, 안개 강도에 따른 보정을 한다. 제안하는 기법은 기존의 기법들과 비교하여 색상의 편향성을 보정하여 가시성뿐만 아니라 영상 내에 색상이 자연스럽게 조화된 결과를 얻었다.

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New Shot Boundary Detection Using Local $X^2$-Histogram and Normalization (지역적 $X^2$-히스토그램과 정규화를 이용한 새로운 샷 경계 검출)

  • Shin, Seong-Yoon
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.103-109
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    • 2007
  • In this paper, we detect shot boundaries using $X^2$-histogram comparison method which have enough spatial information that is more robust to the camera or object motion and produce more precise results. Also, we present normalization method to change Log-Formula and constant that is used for contrast enhancement of image in image processing and apply in difference value. And, present shot boundary detection algorithm to detect shot boundary based on general shot and abrupt shot's characteristic.

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Contrast Improvement Technique Using Variable Stretching based on Densities of Brightness (명암의 밀도에 따른 가변 스트레칭을 이용한 영상대비 개선방법)

  • Lee, Myung-Yoon;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.12
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    • pp.37-45
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    • 2010
  • This paper proposes a novel contrast enhancement method which determines the stretching ranges based on the distribution densities of segmented sub-histogram. In order to enhance the quality of image effectively, the contrast histogram is segmented into sub-histograms based on the density in each brightness region. Then the stretching range of each sub-histogram is determined by analysing its distribution density. The higher density region is extended wider than lower density region in the histogram. This method solves the over stretching problem, because it stretches using density rate of each area on the histogram. To evaluate the performance of the proposed algorithm, the experiments have been carried out on complex contrast images, and its superiority has been confirmed by comparing with the conventional methods.

Shot Boundary Detection Algorithm By Using Pixel and Histogram Information (화소와 히스토그램 정보를 이용한 샷 전환 탐지 알고리즘)

  • Lee, Joon-Goo;Han, Ki-Sun;You, Byoung-Moon;Hwang, Doo-Sung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2012.11a
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    • pp.527-530
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    • 2012
  • 비디오 데이터를 효율적으로 검색, 정렬, 탐색, 분류하기 위해서는 프레임 간의 샷 전환 탐지가 선행되어야 한다. 본 논문에서는 디지털 비디오 데이터의 샷 전환 탐지를 위해 비디오 스트림을 구성하고 있는 각 프레임들 간의 화소 밝기 차이와 히스토그램의 변화를 이용하였다. 플래쉬 등과 같은 인위적이고 급격한 화소 밝기변화에 의한 오류를 최소화하기 위해 샷 전환 탐지 이전에 각 프레임 간의 밝기 보상을 적용하였다. 밝기 보정 된 프레임으로부터 프레임의 서브 블록 간의 지역적 화소 밝기 정보, 그리고 프레임의 화소 밝기 값 히스토그램을 비교하여 샷 전환을 탐지한다. 실험에서 제안된 알고리즘은 국가기록원 소장 비디오에 적용하여 효과가 있음을 보였다.

Face Recognition Using Histograms of Multi-resolution Segments Based on Discriminant Face Descriptor (판별 얼굴 기술자 기반의 다중 해상도 분할 영역 히스토그램을 이용한 얼굴인식 방법)

  • Lee, Jang-yoon;Lee, Yonggeol;Choi, Sang-Il
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.2
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    • pp.97-105
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    • 2016
  • We propose a face recognition method using the histograms of multi-resolution segments in order to effectively utilize the local information of faces. Since the variations in faces can occur in various sizes, the DFD method, which uses the histograms from the sub-regions of the same size, is not effective for obtaining local information of faces. In this paper, we first divide an image into several sub-regions and extract the DFD(Discriminant Face Descriptor) from each sub-region. By dividing each sub-region into several segments with multi-resolution and extracting histograms for each segment, we reduce the loss of local information in the process of recognition. The experimental results for the Yale B, AR, CAS-PEAL-R1 databases show that the proposed method improves the recognition performance compared to the existing DFD based method.

Scene Change Detection Using Local $x-^{2}-Test$ (지역적 $x-^{2}$-테스트를 이용한 장면전환검출 기법)

  • Kim, Yeong-Rye;Rhee, Yang-Won
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.3
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    • pp.193-201
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    • 2006
  • This paper presents a method that allows for detection of all rapid and gradual scene changes. The method features a combination of the current color histogram and the local $X^{2}-test$. For the purpose of this paper, the $X^{2}-test$ scheme outperforming existing histogram-based algorithms was transformed, and a local $X^{2}-test$ in which weights were applied in accordance with the degree of brightness was used to increase detection efficiency in the segmentation of color values. This Method allows for analysis and segmentation of complex time-varying images in the most general and standardized manner possible Experiments were performed to compare the proposed local $X^{2}-test$ method with the current $X^{2}-test$ method.

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Background and Local Histogram-Based Object Tracking Approach (도로 상황인식을 위한 배경 및 로컬히스토그램 기반 객체 추적 기법)

  • Kim, Young Hwan;Park, Soon Young;Oh, Il Whan;Choi, Kyoung Ho
    • Spatial Information Research
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    • v.21 no.3
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    • pp.11-19
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    • 2013
  • Compared with traditional video monitoring systems that provide a video-recording function as a main service, an intelligent video monitoring system is capable of extracting/tracking objects and detecting events such as car accidents, traffic congestion, pedestrian detection, and so on. Thus, the object tracking is an essential function for various intelligent video monitoring and surveillance systems. In this paper, we propose a background and local histogram-based object tracking approach for intelligent video monitoring systems. For robust object tracking in a live situation, the result of optical flow and local histogram verification are combined with the result of background subtraction. In the proposed approach, local histogram verification allows the system to track target objects more reliably when the local histogram of LK position is not similar to the previous histogram. Experimental results are provided to show the proposed tracking algorithm is robust in object occlusion and scale change situation.

Performance Enhancement through Row-Column Cross Scanning in Differential Histogram-based Reversible Watermarking (차이값 히스토그램 기반 가역 워터마킹의 행열 교차 스캐닝을 통한 성능 향상 기법)

  • Yeo, Dong-Gyu;Lee, Hae-Yeoun;Kim, Byeong-Man
    • The KIPS Transactions:PartB
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    • v.18B no.1
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    • pp.1-10
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    • 2011
  • Reversible watermarking inserts watermark into digital media in such a way that visual transparency is preserved, which enables the restoration of the original media from the watermarked one without any loss of media quality. It has various applications, where high capacity and high visual quality are major requirements. This paper presents a new effective multi-round embedding scheme for the differential histogram-based reversible watermarking that satisfies high capacity requirements of the application. The proposed technique exploits the row-column cross scanning to fully utilize the locality of images when multi-round embedding phase to the message inserted image. Through experiments using multiple kinds of test images, we prove that the presented algorithm provides 100% reversibility, effectiveness of multi-round embedding, and higher visual quality, while maintaining the induced-distortion low.

Image Retrieval using Local Color Histogram and Shape Feature (지역별 색상 분포 히스토그램과 모양 특징을 이용한 영상 검색)

  • 정길선;김성만;이양원
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 1999.05a
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    • pp.50-54
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    • 1999
  • This paper is proposed to image retrieval system using color and shape feature. Color feature used to four maximum value feature among the maximum value extracted from local color distribution histogram. The preprocessing of shape feature consist of edge extraction and weight central point extraction and angular sampling. The sum of distance from weight central point to contour and variation and max/min used to shape feature. The similarity is estimated compare feature of query image with the feature of images in database and the candidate of image is retrieved in order of similarity. We evaluate the effectiveness of shape feature and color feature in experiment used to two hundred of the closed image. The Recall and the Precision is each 0.72 and 0.53 in the result of average experiment. So the proposed method is presented useful method.

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