• Title/Summary/Keyword: histogram analysis

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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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A Broken Image Screening Method based on Histogram Analysis to Improve GAN Algorithm (GAN 알고리즘 개선을 위한 히스토그램 분석 기반 파손 영상 선별 방법)

  • Cho, Jin-Hwan;Jang, Jongwook;Jang, Si-Woong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.4
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    • pp.591-597
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    • 2022
  • Recently, many studies have been done on the data augmentation technique as a way to efficiently build datasets. Among them, a representative data augmentation technique is a method of utilizing Generative Adversarial Network (GAN), which generates data similar to real data by competitively learning generators and discriminators. However, when learning GAN, there are cases where a broken pixel image occurs among similar data generated according to the environment and progress, which cannot be used as a dataset and causes an increase in learning time. In this paper, an algorithm was developed to select these damaged images by analyzing the histogram of image data generated during the GAN learning process, and as a result of comparing them with the images generated in the existing GAN, the ratio of the damaged images was reduced by 33.3 times(3,330%).

Study on sea fog detection near Korea peninsula by using GMS-5 Satellite Data (GMS-5 위성자료를 이용한 한반도 주변 해무탐지 연구)

  • 윤홍주
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.4
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    • pp.875-884
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    • 2000
  • Sea fog/stratus is very difficult to detect because of the characteristics of air-sea interaction and locality ,and the scantiness of the observed data from the oceans such as ships or ocean buoys. The aim of our study develops new algorism for sea fog detection by using Geostational Meteorological Satellite-5(GMS-5) and suggests the technics of its continuous detection. In this study, atmospheric synoptic patterns on sea fog day of May, 1999 are classified; cold air advection type(OOUTC, May 10, 1999) and warm air advection type(OOUTC, May 12, 1999), respectively, and we collected two case days in order to analyze variations of water vapor at Osan observation station during May 9-10, 1999.So as to detect daytime sea fog/stratus(OOUTC, May 10, 1999), composite image, visible accumulated histogram method and surface albedo method are used. The characteristic value during day showed A(min) .20% and DA < 10% when visible accumulated histogram method was applied. And the sea fog region which is detected is similar in composite image analysis and surface albedo method. Inland observation which visibility and relative humidity is beneath 1Km and 80%, respectively, at OOUTC, May 10,1999; Poryoung for visble accumulated histogram method and Poryoung, Mokp'o and Kangnung for surface albedo method. In case of nighttime sea fog(18UTC, May 10, 1999), IR accumulated histogram method and Maximum brightness temperature method are used, respectively. Maxium brightness temperature method dectected sea fog better than IR accumulated histogram method with the charateristic value that is T_max < T_max_trs, and then T_max is beneath 700hPa temperature of GDAPS(Global Data Assimilation and Prediction System). Sea fog region which is detected by Maxium brighness temperature method was similar to the result of National Oceanic and Atmosheric Administratio/Advanced Very High Resolution Radiometer (NOAA/AVHRR) DCD(Dual Channel Difference), but usually visibility and relative humidity are not agreed well in inland.

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Multi-camera image feature analysis for virtual space convergence (가상공간 융합을 위한 다중 카메라 영상 특징 분석)

  • Yun, Jong-Ho;Choi, Myung-Ryul;Lee, Sang-Sun
    • Journal of the Korea Convergence Society
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    • v.8 no.5
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    • pp.19-28
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    • 2017
  • In this paper, we propose a method to reduce the difference in image characteristics when multiple camera images are captured for virtual space production. Sixty-four images were used by cross-mounting eight bodies and lenses, respectively. Image analysis compares and analyzes the standard deviation of the histogram and pixel distribution values. As a result of the analysis, it shows different image characteristics depending on the lens or image sensor, though it is a camera of the same model. In this paper, we have adjusted the distribution of the overall brightness value of the image to compensate for this difference. As a result, the average deviation was the maximum of (Indoor: 6.89, outdoor: 24.23), we obtained images with almost no deviation (Indoor: maximum 0.42, outdoor: maximum: 2.73). In the future, we will study and apply more accurate image analysis methods than image brightness distribution.

Neritic Paleocurrent Analysis of Pennsylvanian Tethyan Sea at Samcheog Coalfield, Korea (후기(後期) 석탄기(石炭紀) 테티스해내(海內) 한국 삼척탄전(三涉炭田)의 천해류(淺海流) 분석(分折))

  • Kim, Haang Mook
    • Economic and Environmental Geology
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    • v.11 no.1
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    • pp.21-37
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    • 1978
  • The depositional environment of the Manhang and the Geumcheon Formation of the Pennsylvanian Gomog Croup is revealed to the shallow neritic marine milieu in this paper also as the results of Park (1963), Cheong(1975) and Kim (1976), through the analyses of stratigraphy, paleocurrent, properties of cross-beddings and sedimentational features. The formations contains some possible terrestrial sediments suggesting the paralic environment, which are however not recognized definitely within them. The paleocurrent analysis is made to the Manhang Formation only. The paleocurrent of the formation is known to belong to the shallow neritic longshore current. The paleocurrent analysis is based chiefly on the cross-bedding analysis, and subordinately on the texture of elastic coarse sediments. The paleocurrent mean is determined to $269^{\circ}$, that is, from east to west, of which direction is interpreted to the right angle to the slope of the basinal depository plane and also the parallel with die depositional strike, according to Klein (1960) and Selley's (1968) criteria. The variance value of paleocurrent directions of the Manhang Formation in the whole area studied is 6,374, and the values range from 3,394 to 6,957 according to the dirstricts. The paleocurreut pattern of the whole area shows polymodel, and the patterns in each district range from trimodel to quadrimodel. Those models approach to the shallow marine or paralic model of Tohill and Picard (1966), Picard and High (1968 a), Pisnak (1957) and Pettijohn (1962). The mean value of maximum inclinations of cross-beddings of the whole area is $19.9^{\circ}$ with the standard deviation of 8.4, and ranges from $15.6^{\circ}$ to $21.7^{\circ}$ in the districts. Comparing the histogram showing the frequency distribution of the maximum inclinations of cross-beddings of the Manhang Formation with the Pettijohn's (1962) histogram, it is found that the model approaches to his marine model. The Pennsylvanian Gomog Group of the coalfield is considered to have had been deposited in the pseudogeosynclinal zone on the plateau by the transgression of the Tethyan sea caused by the epirogenic movements during the Pennsylvanian Period.

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Contents-based Image Retrieval Using Color & Edge Information (칼라와 에지 정보를 이용한 내용기반 영상 검색)

  • Park, Dong-Won;An, Syungog;Ma, Ming;Singh, Kulwinder
    • The Journal of Korean Association of Computer Education
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    • v.8 no.1
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    • pp.81-91
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    • 2005
  • In this paper we present a novel approach for image retrieval using color and edge information. We take into account the HSI(Hue, Saturation and Intensity) color space instead of RGB space, which emphasizes more on visual perception. In our system colors in an image are clustered into a small number of representative colors. The color feature descriptor consists of the representative colors and their percentages in the image. An improved cumulative color histogram distance measure is defined for this descriptor. And also, we have developed an efficient edge detection technique as an optional feature to our retrieval system in order to surmount the weakness of color feature. During the query processing, both the features (color, edge information) could be integrated for image retrieval as well as a standalone entity, by specifying it in a certain proportion. The content-based retrieval system is tested to be effective in terms of retrieval and scalability through experimental results and precision-recall analysis.

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An Adaptive Histogram Equalization Based Local Technique for Contrast Preserving Image Enhancement

  • Lee, Joonwhoan;Pant, Suresh Raj;Lee, Hee-Sin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.1
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    • pp.35-44
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    • 2015
  • The main purpose of image enhancement is to improve certain characteristics of an image to improve its visual quality. This paper proposes a method for image contrast enhancement that can be applied to both medical and natural images. The proposed algorithm is designed to achieve contrast enhancement while also preserving the local image details. To achieve this, the proposed method combines local image contrast preserving dynamic range compression and contrast limited adaptive histogram equalization (CLAHE). Global gain parameters for contrast enhancement are inadequate for preserving local image details. Therefore, in the proposed method, in order to preserve local image details, local contrast enhancement at any pixel position is performed based on the corresponding local gain parameter, which is calculated according to the current pixel neighborhood edge density. Different image quality measures are used for evaluating the performance of the proposed method. Experimental results show that the proposed method provides more information about the image details, which can help facilitate further image analysis.

Comparisons of MPEG-7 Texture Descriptors for Iris recognition (MPEG-7 텍스쳐 서술자의 홍채 인식에 대한 성능 비교)

  • Choo, Hyon-Gon;Kim, Whoi-Yul
    • The KIPS Transactions:PartB
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    • v.11B no.4
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    • pp.421-428
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    • 2004
  • There are three texture descriptors in MPEG-7 : Homogeneous Texture, Edge Histogram and Texture Browsing. In this paper, a comparative analysis is presented on the capability of MPEG-7 texture descriptors for iris recognition as part of an MPEG-7 application using descriptors. Through the experiments of comparing the clustering efficiency and error distribution of the descriptors using 560 iris images, their discriminating capabilities for different iris groups are analyzed. The results show that Homogenous Texture descriptor is the best discriminator among three descriptors to recognize the iris pattern. However, compared with the conventional iris recognition methods, it needs more efforts to enhance the results.

Eyebrow Detection Algorithm Using the Histogram Analysis (히스토그램 분석을 이용한 눈썹 검출 알고리즘)

  • 이강호
    • Journal of the Korea Society of Computer and Information
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    • v.7 no.4
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    • pp.46-51
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    • 2002
  • In this paper, I proposed a eyebrow detection algorithm in human face, that is important element in facial recognition. The proposed algorithm consists of four processes: face region detection using color region segmentation. eye detection by template matching, eyebrow candidate region detection in detected eye region, and eyebrow detection by thresholding using the modified histogram that gets luminance value in the candidate region. The test results show that the proposed algorithm can detect eyebrow region very effectively in facial image.

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Symmetry Detection Through Hybrid Use Of Location And Direction Of Edges

  • Koo, Ja Young
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.4
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    • pp.9-15
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    • 2016
  • Symmetry is everywhere in the world around us from galaxy to microbes. From ancient times symmetry is considered to be a reflection of the harmony of universe. Symmetry is not only a significant clue for human cognitive process, but also useful information for computer vision such as image understanding system. Application areas include face detection and recognition, indexing of image database, image segmentation and detection, analysis of medical images, and so on. The technique used in this paper extracts edges, and the perpendicular bisector of any two edge points is considered to be a candidate axis of symmetry. The coefficients of candidate axis are accumulated in the coefficient space. Then the axis of symmetry is determined to be the line for which the coefficient histogram has maximum value. In this paper, an improved method is proposed that utilizes the directional information of edges, which is a byproduct of the edge detection process. Experiment on 20 test images shows that the proposed method performs 22.7 times faster than the original method. In another test on 5 images with 4% salt-and-pepper noise, the proposed method detects the symmetry successfully, while the original method fails. This result reveals that the proposed method enhances the speed and accuracy of detection process at the same time.