• Title/Summary/Keyword: Color Transform Model

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Visibility Enhancement of Underwater Image Using a Color Transform Model (색상 변환 모델을 이용한 수중 영상의 가시성 개선)

  • Jang, Ik-Hee;Park, Jeong-Seon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.5
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    • pp.645-652
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    • 2015
  • In underwater, such as fish farm and sea, turbidity is increased by water droplets and various suspended, therefore light attenuation occurs depending on the depth also caused by the scattering effect of light float. In this paper, in order to improve the visibility of underwater images obtained from these aquatic environment, we propose a visibility enhancement method using a haze removal method based on dark channel prior and a trained color transform model. In order to train a color transform model, we used underwater pattern images captured from Pohang and Yeosu, and to measure the performance of the proposed method, we carried out experiment of visibility enhancement using underwater images collected from Yeosu, Geomundo and Philippines. The results show that the proposed method can improve the visibility of underwater images of various locations.

A Perceptually-Adaptive High-Capacity Color Image Watermarking System

  • Ghouti, Lahouari
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.1
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    • pp.570-595
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    • 2017
  • Robust and perceptually-adaptive image watermarking algorithms have mainly targeted gray-scale images either at the modeling or embedding levels despite the widespread availability of color images. Only few of the existing algorithms are specifically designed for color images where color correlation and perception are constructively exploited. In this paper, a new perceptual and high-capacity color image watermarking solution is proposed based on the extension of Tsui et al. algorithm. The $CIEL^*a^*b^*$ space and the spatio-chromatic Fourier transform (SCFT) are combined along with a perceptual model to hide watermarks in color images where the embedding process reconciles between the conflicting requirements of digital watermarking. The perceptual model, based on an emerging color image model, exploits the non-uniform just-noticeable color difference (NUJNCD) thresholds of the $CIEL^*a^*b^*$ space. Also, spread-spectrum techniques and semi-random low-density parity check codes (SR-LDPC) are used to boost the watermark robustness and capacity. Unlike, existing color-based models, the data hiding capacity of our scheme relies on a game-theoretic model where upper bounds for watermark embedding are derived. Finally, the proposed watermarking solution outperforms existing color-based watermarking schemes in terms of robustness to standard image/color attacks, hiding capacity and imperceptibility.

An Intelligent Video Image Segmentation System using Watershed Algorithm (워터쉐드 알고리즘을 이용한 지능형 비디오 영상 분할 시스템)

  • Yang, Hwang-Kyu
    • The Journal of the Korea institute of electronic communication sciences
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    • v.5 no.3
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    • pp.309-314
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    • 2010
  • In this paper, an intelligent security camera over internet is proposed. Among ISC methods, watersheds based methods produce a good performance in segmentation accuracy. But traditional watershed transform has been suffered from over-segmentation due to small local minima included in gradient image that is input to the watershed transform. And a zone face candidates of detection using skin-color model. last step, face to check at face of candidate location using SVM method. It is extract of wavelet transform coefficient to the zone face candidated. Therefore, it is likely that it is applicable to read world problem, such as object tracking, surveillance, and human computer interface application etc.

The emotional evaluation of color pattern based on information fusion (정보융합 기법을 이용한 칼라 패턴의 감성 평가)

  • 김성환;엄경배;이준환
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.23-27
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    • 2000
  • In this paper, we propose an emotional evaluation model based on information fusion. This model can transform the physical features of a color pattern to the emotional features. Our proposed model consists of the fuzzy logic system and neural network model. The evaluation values produced by them were fused. The model shows comparable performances to the neural network and fuzzy logic system for the approximation of the nonlinear transforms. We believe the evaluated results of a color pattern can be used to the emotion-based color image retrievals.

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Robust pattern watermarking using wavelet transform and multi-weights (웨이브렛 변환과 다중 가중치를 이용한 강인한 패턴 워터마킹)

  • 김현환;김용민;김두영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.3B
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    • pp.557-564
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    • 2000
  • This paper presents a watermarking algorithm for embedding visually recognizable pattern (Mark, Logo, Symbol, stamping or signature) into the image. first, the color image(RGB model)is transformed in YCbCr model and then the Y component is transformed into 3-level wavelet transform. Next, the values are assembled with pattern watermark. PN(pseudo noise) code at spread spectrum communication method and mutilevel watermark weights. This values are inserted into discrete wavelet domain. In our scheme, new calculating method is designed to calculate wavelet transform with integer value in considering the quantization error. and we used the color conversion with fixed-point arithmetic to be easy to make the hardware hereafter. Also, we made the new solution using mutilevel threshold to robust to common signal distortions and malicious attack, and to enhance quality of image in considering the human visual system. the experimental results showed that the proposed watermarking algorithm was superior to other similar water marking algorithm. We showed what it was robust to common signal processing and geometric transform such as brightness. contrast, filtering. scaling. JPEG lossy compression and geometric deformation.

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Automatic Color Palette Extraction for Paintings Using Color Grouping and Clustering (색상 그룹핑과 클러스터링을 이용한 회화 작품의 자동 팔레트 추출)

  • Lee, Ik-Ki;Lee, Chang-Ha;Park, Jae-Hwa
    • Journal of KIISE:Computer Systems and Theory
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    • v.35 no.7
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    • pp.340-353
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    • 2008
  • A computational color palette extraction model is introduced to describe paint brush objectively and efficiently. In this model, a color palette is defined as a minimum set of colors in which a painting can be displayed within error allowance and extracted by the two step processing of color grouping and major color extraction. The color grouping controls the resolution of colors adaptively and produces a basic color set of given painting images. The final palette is obtained from the basic color set by applying weighted k-means clustering algorithm. The extracted palettes from several famous painters are displayed in a 3-D color space to show the distinctive palette styles using RGB and CIE LAB color models individually. And the two experiments of painter classification and color transform of photographic image has been done to check the performance of the proposed method. The results shows the possibility that the proposed palette model can be a computational color analysis metric to describe the paint brush, and can be a color transform tool for computer graphics.

Integrated Method for Text Detection in Natural Scene Images

  • Zheng, Yang;Liu, Jie;Liu, Heping;Li, Qing;Li, Gen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.11
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    • pp.5583-5604
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    • 2016
  • In this paper, we present a novel image operator to extract textual information in natural scene images. First, a powerful refiner called the Stroke Color Extension, which extends the widely used Stroke Width Transform by incorporating color information of strokes, is proposed to achieve significantly enhanced performance on intra-character connection and non-character removal. Second, a character classifier is trained by using gradient features. The classifier not only eliminates non-character components but also remains a large number of characters. Third, an effective extractor called the Character Color Transform combines color information of characters and geometry features. It is used to extract potential characters which are not correctly extracted in previous steps. Fourth, a Convolutional Neural Network model is used to verify text candidates, improving the performance of text detection. The proposed technique is tested on two public datasets, i.e., ICDAR2011 dataset and ICDAR2013 dataset. The experimental results show that our approach achieves state-of-the-art performance.

Development of Color Inspection System of Printed Texture using Scanner (스캐너를 이용한 직물의 색상검사기 개발)

  • 조지승;정병묵;박무진
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.8
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    • pp.70-75
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    • 2003
  • It is very important to inspect the color of printed texture in the textile process. The standard colorimetric system used for the recognition of the color in the textile industry. It uses XYZ color system defined by CIE (Commission Internationale de 1Eclairage), but is too expensive. Therefore, in this paper, we propose a color inspection system of the printed texture using a color scanner. Because the scanner uses RGB value for color, it is necessary the mapping from RGB to XYZ. However, the mapping is not simple, and the scanner has even positional deviation because of the geometric characteristics. To transform from RGB to XYZ, we used a NN (neural network) model and also compensated the positional deviation. In real experiments, we could get fairly exact XYZ value from the proposed color inspection system in spite of using a color scanner with large measuring area.

Study on Effective Lane Detection Using Hough Transform and Lane Model (허프변환과 차선모델을 이용한 효과적인 차선검출에 관한 연구)

  • Kim, Gi-Seok;Lee, Jin-Wook;Cho, Jae-Soo
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.34-36
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    • 2009
  • This paper proposes an effective lane detection algorithm using hugh transform and lane model. The proposed lane detection algorithm includes two major components, i.e., lane marks segmentation and an exact lane extraction using a novel postprocessing technique. The first step is to segment lane marks from background images using HSV color model. Then, a novel postprocessing is used to detect an exact lane using Hugh transform and lane models(linear and curved lane models). The postprocessing consists of three parts, i.e, thinning process, Hugh Transform and filtering process. We divide input image into three regions of interests(ROIs). Based on lane curve function(LCF), we can detect an exact lane from various extracted lane lines. The lane models(linear and curved lane mode]) are used in order to judge whether each lane segment is fit or not in each ROIs. Experimental results show that the proposed scheme is very effective in lane detection.

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A Color Image Watermarking Method for Embedding Audio Signal

  • Kim Sang Jin;Kim Chung Hwa
    • Proceedings of the IEEK Conference
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    • 2004.08c
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    • pp.631-635
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    • 2004
  • The rapid development of digital media and communication network urgently brings about the need of data certification technology to protect IPR (Intellectual property right). This paper proposed a new watermarking method for embedding contents owner's audio signal in order to protect color image IPR. Since this method evolves the existing static model and embeds audio signal of big data, it has the advantage of restoring signal transformed due to attacks. Three basic stages of watermarking include: 1) Encode analogue ID owner's audio signal using PCM and create new 3D audio watermark; 2) Interleave 3D audio watermark by linear bit expansion and 3) Transform Y signal of color image into wavelet and embed interleaved audio watermark in the low frequency band on the transform domain. The results demonstrated that the audio signal embedding in color image proposed in this paper enhanced robustness against lossy JPEG compression, standard image compression and image cropping and rotation which remove a part of image.

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