• Title/Summary/Keyword: Color Distribution Histogram

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Efficient Color Feature Information Extraction Method for Color Histogram-based Image Retrieval (칼라 히스토그램 기반 영상 검색을 위한 효율적인 칼라 특징 정보 추출 기법)

  • 이호영;김영태;김희수;배태면;하영호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.8B
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    • pp.1413-1423
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    • 2000
  • Color distribution is changed according to the variation of illumination position and illumination color. Therefore, even if images are relevant each other, retrieval accuracy is degraded. In this paper, we propose the image retrieval method using color information excluded illumination component. The proposed dynamic range control method removes the shadow region generated by change of illumination position to increase the color discrimination power. To exclude the illuminant color, we use the diffuse reflection component of object and gray world assumption. The experimental results show that the color histogram method using color information excluded illuminant has higher retrieval accuracy than conventional color histogram using the color information of input image.

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Face Detection Algorithm Using Color Distribution Matching (영상의 색상 분포 정합을 이용한 얼굴 검출 알고리즘)

  • Kwon, Seong-Geun
    • Journal of Korea Multimedia Society
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    • v.16 no.8
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    • pp.927-933
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    • 2013
  • Face detection algorithm of OpenCV recognizes the faces by Haar matching between input image and Haar features which are learned through a set of training images consisting of many front faces. Therefore the face detection method by Haar matching yields a high face detection rate for the front faces but not in the case of the pan and deformed faces. On the assumption that distributional characteristics of color histogram is similar even if deformed or side faces, a face detection method using the histogram pattern matching is proposed in this paper. In the case of the missed detection and false detection caused by Haar matching, the proposed face detection algorithm applies the histogram pattern matching with the correct detected face area of the previous frame so that the face region with the most similar histogram distribution is determined. The experiment for evaluating the face detection performance reveals that the face detection rate was enhanced about 8% than the conventional method.

Contrast Enhancement using Dynamic Range Separate Histogram Equalization (동적영역 분할을 이용한 명암비 향상기법)

  • Kang, Hyun-Woo;Park, Gyu-Hee;Hwang, Bo-Hyun;Yun, Jong-Ho;Choi, Myung-Ryul
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.917-918
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    • 2008
  • Histogram Equalization (HE) method is widely used for contrast enhancement. However, HE often introduce washed out appearance or color distortion due to the over enhancement in contrast. In this paper, Dynamic Range Separate Histogram Equalization (DRSHE) is proposed for contrast enhancement. DRSHE reconfigures the dynamic range of histogram using probability distribution ratio. The experimental results show that DRSHE suppresses the washed out appearance or color distortion and preserves naturalness of the original image compared with conventional methods.

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Object Modeling with Color Arrangement for Region-Based Tracking

  • Kim, Dae-Hwan;Jung, Seung-Won;Suryanto, Suryanto;Lee, Seung-Jun;Kim, Hyo-Kak;Ko, Sung-Jea
    • ETRI Journal
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    • v.34 no.3
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    • pp.399-409
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    • 2012
  • In this paper, we propose a new color histogram model for object tracking. The proposed model incorporates the color arrangement of the target that encodes the relative spatial distribution of the colors inside the object. Using the color arrangement, we can determine which color bin is more reliable for tracking. Based on the proposed color histogram model, we derive a mean shift framework using a modified Bhattacharyya distance. In addition, we present a method of updating an object scale and a target model to cope with changes in the target appearance. Unlike conventional mean shift based methods, our algorithm produces satisfactory results even when the object being tracked shares similar colors with the background.

The Brand Image Retrieval System Based on Color and Shape (컬러와 형태에 기반을 둔 상표 영상 검색 시스템)

  • Shin, Seong-Yoon;Pyo, Seong-Bae
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.3
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    • pp.167-172
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    • 2006
  • An image retrieval system retrieves and offers same of similar image based on various features of image. This paper present a brand image retrieval system based on color and shape of image. We use the image for a color information by dividing into the area and extracting the area color distribution histogram. We use for the shape information by preprocessing of the boundary extraction, the centroid extraction, angular sampling etc. and calculating of the sum of the distance from the centroid to the boundary, the standard deviation, and the rate of long axis to short axis. We accomplish the retrieval through a similarity measurement by using the color and shape information which is extracted in this way.

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Development to Image Search Algorithm for JPEG2000 (JPEG2000기반 검색 알고리즘 개발)

  • Cho, Jae-Hoon;Kim, Young-Seop
    • Journal of the Semiconductor & Display Technology
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    • v.6 no.2 s.19
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    • pp.53-57
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    • 2007
  • In this paper, a new content-based color image retrieval method is proposed, in which both the color content and the spatial relationship of image have been taken into account. In order to represent the spatial distribution information of image, a disorder matrix, which has the invariance to the rotation and translation of the image content, has been designed. This is based on multi-resolution color-spatial information. We present our algorithm in the following section, and then verified the search results with comparison to other methods, such as color histogram, wavelet histogram, correlogram and wavelet correlogram. Experimental results with various types of images show that the proposed method not only achieves a high image retrieval performance but also improve the retrieval precision.

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Image Retrieval Using the Color Co-occurrence Histogram Describing the Size and Coherence of the Homogeneous Color Region (칼라 영역의 크기와 뭉침을 기술하는 칼라 동시발생 히스토그램을 이용한 영상검색)

  • An Myung-Seok;Cho Seok-Je
    • The KIPS Transactions:PartB
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    • v.13B no.3 s.106
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    • pp.275-282
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    • 2006
  • For the efficient image retrieval, the method has studied that uses color distribution and relations between pixels. This paper presents the color descriptor that stands high above the others in image retrieval capacity. It is based on color co-occurrence histogram that the diagonal part and the non-diagonal part are attached the weight and modified to energy of color co-occurrence histogram, and the number of bins with petty worth have little influence is curtailed. It's verified by analysis that the diagonal part carries size information of homogeneous color region and the non-diagonal part does information about the coherence of it, Moreover the non-diagonal part is more influential than diagonal part in survey of similarity between images. So, the non-diagonal part is attached more weight than the diagonal part as a result of the research. The experiments validate that the proposed descriptor shows better image retrieval performance when the weight for non-diagonal part is set to the value between 0.7 and 0.9.

Distinction of Color Similarity for Clothes based on the LBG Algorithm (LBG 알고리즘 기반의 의상 색상 유사성 판별)

  • Ju, Hyung-Don;Hong, Min;Cho, We-Duke;Moon, Nam-Mee;Choi, Yoo-Joo
    • Journal of Internet Computing and Services
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    • v.9 no.5
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    • pp.117-130
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    • 2008
  • This paper proposes a stable and robust method to distinct the color similarity for clothes using the LBG algorithm under various light sources, Since the conventional methods, such as the histogram intersection and the accumulated histogram, are profoundly sensitive to the changing of light environments, the distinction of color similarity for the same cloth can be different due to the complicated light sources. To reduce the effects of the light sources, the properties of hue and saturation which consistently sustain the characteristic of the color under the various changes of light sources are analyzed to define the characteristic of the color distribution. In a two-dimensional space determined by the properties of hue and saturation, the LBG algorithm, a non-parametric clustering approach, is applied to examine the color distribution of images for each clothes. The color similarity of images is defined by the average of Euclidean distance between the mapping clusters which are calculated from the result of clustering of both images. To prove the stability of the proposed method, the results of the color similarity between our method and the traditional histogram analysis based methods are compared using a dozen of cloth examples that obtained under different light environments. Our method successively provides the classification between the same cloth image pair and the different cloth image pair and this classification of color similarity for clothe images obtains the 91.6% of success rate.

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Histogram Equalization Based Color Space Quantization for the Enhancement of Mean-Shift Tracking Algorithm (실시간 평균 이동 추적 알고리즘의 성능 개선을 위한 히스토그램 평활화 기반 색-공간 양자화 기법)

  • Choi, Jangwon;Choe, Yoonsik;Kim, Yong-Goo
    • Journal of Broadcast Engineering
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    • v.19 no.3
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    • pp.329-341
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    • 2014
  • Kernel-based mean-shift object tracking has gained more interests nowadays, with the aid of its feasibility of reliable real-time implementation of object tracking. This algorithm calculates the best mean-shift vector based on the color histogram similarity between target model and target candidate models, where the color histograms are usually produced after uniform color-space quantization for the implementation of real-time tracker. However, when the image of target model has a reduced contrast, such uniform quantization produces the histogram model having large values only for a few histogram bins, resulting in a reduced accuracy of similarity comparison. To solve this problem, a non-uniform quantization algorithm has been proposed, but it is hard to apply to real-time tracking applications due to its high complexity. Therefore, this paper proposes a fast non-uniform color-space quantization method using the histogram equalization, providing an adjusted histogram distribution such that the bins of target model histogram have as many meaningful values as possible. Using the proposed method, the number of bins involved in similarity comparison has been increased, resulting in an enhanced accuracy of the proposed mean-shift tracker. Simulations with various test videos demonstrate the proposed algorithm provides similar or better tracking results to the previous non-uniform quantization scheme with significantly reduced computation complexity.

Image Retrieval via Query-by-Layout Using MPEG-7 Visual Descriptors

  • Kim, Sung-Min;Park, Soo-Jun;Won, Chee-Sun
    • ETRI Journal
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    • v.29 no.2
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    • pp.246-248
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    • 2007
  • Query-by-example (QBE) is a well-known method for image retrieval. In reality, however, an example image to be used for the query is rarely available. Therefore, it is often necessary to find a good example image to be used for the query before applying the QBE method. Query-by-layout (QBL) is our proposal for that purpose. In particular, we make use of the visual descriptors such as the edge histogram descriptor (EHD) and the color layout descriptor (CLD) in MPEG-7. Since image features of the CLD and the EHD can be localized in terms of a$4{\times}4$ sub-image, we can specify image features such as color and edge distribution on each sub-image separately for image retrieval without a query image. Experimental results show that the proposed query method can be used to retrieve a good image as a starting point for further QBE-based image retrieval.

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