• Title/Summary/Keyword: 컬러 히스토그램

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An Efficient Shaking Correction Techniques for Image Stabilization of Moving Vehicles (이동차량 영상 안정화를 위한 효율적인 흔들림 보정 기법)

  • Hong, Sung-Il;Lin, Chi-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.3
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    • pp.155-162
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    • 2014
  • In this paper, we propose an efficient shaking correction techniques for a moving vehicle image stabilization. The proposed shaking correction techniques was calculated cumulative histogram for the conversion and the separating information via color separation of video image frame of the input received. And it were to matching the histogram for match the color information as compensation result of the shaking vehicle video imaging. In this paper, the proposed the shaking correction techniques was obtained to the restoration result when compared to the existing shaking correction techniques that the smallest noise and better the naturalness of image through stabilization of luminance level and color level. Also, the imaging stabilization method was demonstrated the efficiency compared to other methods through to the real-time processing without the use of the memory.

Nucleus Recognition of Uterine Cervical Pap-Smears using Fuzzy Reasoning Rule (퍼지 추론 규칙을 이용한 자궁 경부진 핵 인식)

  • Kim, Kwang-Baek;Song, Doo-Heon
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.3
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    • pp.179-187
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    • 2008
  • In this paper, we apply a set of algorithms to classily normal and cancer nucleus from uterine cervical pap-smear images. First, we use lightening compensation algorithm to restore color images that have defamation through the process of obtaining $1{\times}400$ microscope magnification. Then, we remove the background from images with the histogram distributions of RGB regions. We extract nucleus areas from candidates by applying histogram brightness, Kapur method, and our own 8-direction contour tracing algorithm. Various binarization, cumulative entropy, masking algorithms are used in that process. Then, we are able to recognize normal and cancer nucleus from those areas by using three morphological features - directional information, the size of nucleus, and area ratio - with fuzzy membership functions and deciding rules we devised. The experimental result shows our method has low false recognition rate.

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Cut Detection Algorithm Using the Characteristic Of Wavelet Coefficients in Each Subband (대역별 웨이블릿 계수특성을 이용한 장면전환점 검출기법)

  • Moon Young ho;No Jung Jin;Yoo Ji sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.10C
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    • pp.1414-1424
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    • 2004
  • In this paper, an algorithm using wavelet transform for detecting a cut that is a radical scene transition point, and fade and dissolve that are gradual scene transition points is proposed. The conventional methods using wavelet transform for this purpose is using features in both spatial and frequency domain. But in the proposed algorithm, the color space of an input image is converted to YUV and then luminance component Y is transformed in frequency domain using 2-level lifting. Then, the histogram of only low frequency subband that may contain some spatial domain features is compared with the previous one. Edges obtained from other higher bands can be divided into global, semi-global and local regions and the histogram of each edge region is compared. The experimental results show the performance improvement of about 17% in recall and 18% in precision and also show a good performance in fade and dissolve detection.

Video-based Intelligent Unmanned Fire Surveillance System (영상기반 지능형 무인 화재감시 시스템)

  • Jeon, Hyoung-Seok;Yeom, Dong-Hae;Joo, Young-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.4
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    • pp.516-521
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    • 2010
  • In this paper, we propose a video-based intelligent unmanned fire surveillance system using fuzzy color models. In general, to detect heat or smoke, a separate device is required for a fire surveillance system, this system, however, can be implemented by using widely used CCTV, which does not need separate devices and extra cost. The systems called video-based fire surveillance systems use mainly a method extracting smoke or flame from an input image only. The smoke is difficult to extract at night because of its gray-scale color, and the flame color depends on the temperature, the inflammable, the size of flame, etc, which makes it hard to extract the flame region from the input image. This paper deals with a intelligent fire surveillance system which is robust against the variation of the flame color, especially at night. The proposed system extracts the moving object from the input image, makes a decision whether the object is the flame or not by means of the color obtained by fuzzy color model and the shape obtained by histogram, and issues a fire alarm when the flame is spread. Finally, we verify the efficiency of the proposed system through the experiment of the controlled real fire.

Retinex Algorithm Improvement for Color Compensation in Back-Light Image Efficently (역광 이미지의 효율적인 컬러 색상 보정을 위한 Retinex 알고리즘의 성능 개선)

  • Kim, Young-Tak;Yu, Jae-Hyoung;Hahn, Hern-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.1
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    • pp.61-69
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    • 2011
  • This paper proposes a new algorithm that improve color component of compensated image using Retinex method for back-light image. A back-light image has two regions, one of the region is too bright and the other one is too dark. If an back-light image is improved contrast using Retinex method, it loses color information in the part of brightness of the image. In order to make up loss information, proposed algorithm adds color components from original image. The histogram can be divided three parts that brightness, darkness, midway using K-mean (k=3) algorithm. For the brightness, it is used color information of the original image. For the darkness, it is converted using by Retinex method. The midway region is mixed between original image and Retinex result image in the ratio of histogram. The ratio is determined by distance from dark area. The proposed algorithm was tested on nature back-light images to evaluate performance, and the experimental result shows that proposed algorithm is more robust than original Retinex algorithm.

Adaptive LSB Steganography for High Capacity in Spatial Color Images (컬러이미지 대상 고용량 적응형 LSB 스테가노그라피)

  • Lee, Haeyoung
    • Journal of the Korea Computer Graphics Society
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    • v.24 no.1
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    • pp.27-33
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    • 2018
  • This paper presents a new adaptive LSB steganography for high capacity in spatial color images. The number of least signi ficant bit (LSB) of each RGB component in a color image pixel, to replace with the data bits to be hidden, was determine d through analysis of the worst case peak signal noise ratio (PSNR). In addition, the combination of the number of bits is determined adaptively according to image content. That is, 70% of the data to be hidden is proposed to be replaced with 3 bit LSB of two components, 2 bit LSB of the rest component, and 30% be replaced with 4 bit LSB of each RGB compon ent. To find edge areas in an image, delta sorting in local area is also suggested. Using the proposed method, the data cap acity is 9.2 bits per pixel (bpp). The average PSNR value of the tested images with concealed data of up to 60Kbyte was 43.9 db and also natural histograms were generated.

Object Tracking Algorithm Using Weighted Color Centroids Shifting (가중 컬러 중심 이동을 이용한 물체 추적 알고리즘)

  • Choi, Eun-Cheol;Lee, Suk-Ho;Kang, Moon-Gi
    • Journal of Broadcast Engineering
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    • v.15 no.2
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    • pp.236-247
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    • 2010
  • Recently, mean shift tracking algorithms have been proposed which use the information of color histogram together with some spatial information provided by the kernel. In spite of their fast speed, the algorithms are suffer from an inherent instability problem which is due to the use of an isotropic kernel for spatiality and the use of the Bhattacharyya coefficient as a similarity function. In this paper, we analyze how the kernel and the Bhattacharyya coefficient can arouse the instability problem. Based on the analysis, we propose a novel tracking scheme that uses a new representation of the location of the target which is constrained by the color, the area, and the spatiality information of the target in a more stable way than the mean shift algorithm. With this representation, the target localization in the next frame can be achieved by one step computation, which makes the tracking stable, even in difficult situations such as low-rate-frame environment, and partial occlusion.

Improved Text Recognition using Analysis of Illumination Component in Color Images (컬러 영상의 조명성분 분석을 통한 문자인식 성능 향상)

  • Choi, Mi-Young;Kim, Gye-Young;Choi, Hyung-Il
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.3
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    • pp.131-136
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    • 2007
  • This paper proposes a new approach to eliminate the reflectance component for the detection of text in color images. Color images, printed by color printing technology, normally have an illumination component as well as a reflectance component. It is well known that a reflectance component usually obstructs the task of detecting and recognizing objects like texts in the scene, since it blurs out an overall image. We have developed an approach that efficiently removes reflectance components while preserving illumination components. We decided whether an input image hits Normal or Polarized for determining the light environment, using the histogram which consisted of a red component. We were able to go ahead through the ability to extract by reducing the blur phenomenon of text by light because reflection component by an illumination change and removed it and extracted text. The experimental results have shown a superior performance even when an image has a complex background. Text detection and recognition performance is influenced by changing the illumination condition. Our method is robust to the images with different illumination conditions.

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A New Scene Change Detection Method using Color Layout Descriptor (Color Layout Descriptor를 이용한 새로운 장면전환검출 방법)

  • Kim, Soo-Young;Won, Jong-Un;Oh, Sang-Keun;Park, Kil-Houm
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.05b
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    • pp.931-934
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    • 2003
  • 본 논문에서는 동영상 내용 기반 검색을 위한 표준 인덱스인 color layout descriptor(CLD)에 기반한 새로운 장면전환검출 방법을 제안한다. 제안한 방법은 입력 영상을 $8{\times}8$ 블록으로 나누고, 그 블록을 대표하는 대표컬러를 선택하여 DCT 변환 후 추출된 DC, AC 계수에 가중치를 부여한 다음 슬라이딩 윈도우를 적용시켜 장면 전환을 검출한다. 이러한 방법은 영상의 전체적인 특성과 국부적인 특성을 동시에 반영하므로, 조명변화나 물체의 움직임에 민감했던 기존 대표적인 방법인 히스토그램 기반 방법과 에지 변화율을 이용한 방법들이 가지는 문제점을 보완할 수 있다. 또한 제안한 방법은 비디오 검색을 위한 MPEG-7 의 검색 서술자 중의 하나인 CLD를 이용하는데 이러한 CLD 는 컬러의 공간적 분포를 잘 설명하므로 MPEG-7 을 위한 검색 서술자에 적합한 장면전환검출 및 검색이 이루어질 수 있다. 제안한 방법을 실험한 결과 기존의 방법보다 장면전환 검출율이 높게 나타났다.

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Content- based Image Retrieval using Fuzzy Integral (퍼지 적분을 이용한 내용기반 영상 검색)

  • Kim, Dong-Woo;Song, Young-Jun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.2
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    • pp.203-208
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    • 2006
  • The management of image information settles as an important field with the advent of multimedia age and we are in need of the effective retrieval method to manage systematically image information. This paper has complemented the problem caused by the absence of space information that is a weak point of the existing color histogram method by assigning regions of features, and raised accuracy by adding texture and shape information. And existing methods using multiple features have problems that the retrieval process is embarrassed because each weight is set up manually. So we has solved these problems by assignment of weight applying fuzzy integral. As a result of experimenting with 1,000 color images, the proposed method showed better precision and recall than the existing method.